Quality Jobs in Chennai

Quality Data Analyst – Electrical Hardware Engineering, Warranty Analytics | KPI Automation | Design Assessment | AI Adoption

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our team. This role will focus on leveraging data analysis and advanced techniques to support our Electrical Hardware Engineering, Warranty Analytics, KPI Automation, Design Assessment, and AI Adoption initiatives within the Automotive / Technology industry. The ideal candidate will possess a strong analytical background and a passion for driving data-driven decisions. Key Responsibilities This role will be responsible for a range of tasks including data analysis, visualization, and reporting to support quality initiatives. The candidate will be expected to identify trends, anomalies, and opportunities for improvement within warranty data, cost trends, and design performance. They will also be involved in the automation of KPI reporting and the implementation of AI -assisted analytics to enhance predictive quality and drive corrective action management . Required Skills & Qualifications Data Analysis: Demonstrated ability to extract, clean, and analyze large datasets to identify meaningful insights and trends. Data Visualization: Proficiency in creating compelling and informative data visualizations using tools such as Power BI and Excel Analytics to communicate complex information effectively. Dashboarding & KPI Reporting: Experience in designing and developing interactive dashboards and automated KPI reports to track key performance indicators and monitor quality metrics. Data Storytelling: Ability to translate data insights into clear and concise narratives that resonate with stakeholders and drive informed decision-making. SQL: Strong proficiency in SQL for data extraction, manipulation, and analysis. Python: Experience using Python for data analysis, scripting, and automation. Databricks: Familiarity with Databricks for data processing and analytics. Power Automate: Experience with Power Automate for workflow automation and data integration. Warranty Data Analytics: Expertise in analyzing warranty data to identify root causes of failures, predict future trends, and optimize product designs. Cost Trend Analysis: Ability to analyze cost trends to identify areas for cost reduction and process improvement. KPI Automation: Experience in automating KPI reporting and data collection processes. Multi-Source Data Integration: Ability to integrate data from multiple sources to create a comprehensive view of quality performance. AI-Assisted Analytics: Experience leveraging AI and Generative AI techniques to enhance data analysis and predictive modeling. Predictive Quality: Ability to apply statistical methods and machine learning algorithms to predict product quality and identify potential issues proactively. Anomaly Detection: Experience in identifying and investigating anomalies in data to uncover potential quality problems. Root Cause Analysis: Expertise in conducting root cause analysis to identify the underlying causes of quality issues. Corrective Action Management: Ability to develop and implement corrective action plans to address quality issues and prevent recurrence. DFMEA, DRBFM, APQP: Familiarity with DFMEA , DRBFM , and APQP methodologies for design and process improvement. Statistical Tools: Proficiency in using various statistical tools for data analysis and quality control. Structured Problem Solving: Ability to apply structured problem-solving techniques to identify and resolve quality issues. Process Optimization: Experience in identifying and implementing process optimization initiatives to improve quality and efficiency. Lean & Six Sigma: Knowledge of Lean and Six Sigma principles for continuous improvement. Quality Tools: Familiarity with various quality tools and techniques for data analysis and problem-solving. Issue Management: Ability to effectively manage and track quality issues to resolution. Warranty Management: Experience in managing warranty claims and analyzing warranty data. Field Quality Analysis: Ability to analyze field quality data to identify trends and patterns. Design Assessment: Ability to conduct design assessments to identify potential quality risks and improve product designs. Design Integrity: Understanding of design integrity principles and their impact on product quality. Design Robustness: Ability to evaluate and improve the design robustness of products. Lessons Learned Deployment: Ability to capture and deploy lessons learned from quality issues to prevent recurrence. Analytical Skills: Strong analytical skills with the ability to interpret data and draw meaningful conclusions. Problem-Solving Skills: Excellent problem-solving skills with the ability to identify and resolve complex quality issues. Data Interpretation Skills: Ability to accurately interpret data and translate it into actionable insights. Communication Skills: Excellent communication skills with the ability to effectively communicate technical information to both technical and non-technical audiences. Stakeholder Management: Ability to build and maintain relationships with key stakeholders . Leadership-Ready Presentation Skills: Ability to deliver compelling and persuasive presentations to senior management. Qualifications: Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline. What We Offer Experience Required: 5 - 10 years of relevant experience. Salary:

Material Planner - Exports (IRF)

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly motivated and experienced Material Planner to join our team in Chennai. This role will focus on export-related material planning within the Automotive industry. The position supports one opening. Key Responsibilities The Material Planner - Exports (IRF) will be responsible for managing and optimizing material flow related to exports, ensuring timely and efficient delivery while maintaining high-quality standards. This includes managing Design Change Management , Serial Life Management , and ensuring adherence to Quality protocols. Required Skills & Qualifications The ideal candidate will possess a strong foundation in material planning principles and a proven ability to manage complex supply chains. A Graduate degree in Engineering is required. Serial Life Management: Demonstrated ability to manage material lifecycles, ensuring proper tracking and adherence to specifications throughout the export process. Design Change Management: Experience in managing and implementing design changes, assessing their impact on material planning and ensuring smooth transitions. Supply Chain Knowledge: A comprehensive understanding of supply chain principles, including sourcing, procurement, and logistics. Supply Chain Flow Management: Ability to optimize material flow, identify bottlenecks, and implement solutions to improve efficiency. Packaging: Knowledge of packaging requirements and best practices for export materials. Quality: A commitment to maintaining high-quality standards throughout the material planning process. SAP: Proficiency in using SAP for material planning and inventory management. MRP: Experience with MRP (Material Requirements Planning) techniques to forecast demand and plan material availability. EDI: Familiarity with EDI (Electronic Data Interchange) for seamless communication with suppliers and customers. Analytical Skills: Strong analytical skills to assess data, identify trends, and make informed decisions. Problem-Solving Skills: Ability to effectively identify and resolve material planning challenges. Communication Skills: Excellent written and verbal communication skills to effectively collaborate with stakeholders. Team Player: Ability to work effectively as part of a team to achieve common goals. Time Oriented: Demonstrated ability to manage time effectively and meet deadlines. Leadership: Potential to provide guidance and support to junior team members. Intercultural Awareness: Ability to work effectively with individuals from diverse cultural backgrounds. Synthesis Oriented: Ability to integrate information from various sources to create a cohesive plan. Facilitator: Ability to facilitate discussions and reach consensus among stakeholders. Experience Required: 3 - 5 years of experience in material planning, preferably within the automotive industry. This level of experience indicates a level of seniority requiring a proactive and self-directed approach to problem-solving and a demonstrated ability to manage complex material planning processes. What We Offer Salary:

Virtual Analysis Engineer L2 Safety

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and motivated Virtual Analysis Engineer L2 Safety to join our team. This is a remote position within the Automobile industry. The ideal candidate will possess a strong analytical background and experience in performing virtual analysis to ensure the safety and performance of our vehicles. Key Responsibilities The Virtual Analysis Engineer L2 Safety will be responsible for conducting comprehensive CAE analysis , contributing to design reviews , and identifying opportunities for structural improvements . This role requires a proactive approach to problem-solving, clear communication of findings and lessons learned , and a commitment to teamwork . Regular project updates will be essential, ensuring stakeholders are informed of progress and any potential challenges. Required Skills & Qualifications Education: A B.E , B.Tech (Mechanical, Automobile), M.E , or M.Tech degree is required. Experience: 3 - 7 years of experience in a related field is expected, demonstrating a solid foundation in virtual analysis and a proven ability to contribute effectively to a team. CAE Analysis: Proficiency in performing CAE analysis , including Occupant simulations and analysis at both Vehicle level and Sled level . Model Refinement & Quality Assessment: Experience in model refinement and rigorous quality assessment of simulation results. Analytical & Problem-Solving Skills: Demonstrated analytical skills and problem-solving skills , with the ability to identify root causes and propose effective solutions. Engineering Fundamentals: A strong understanding of Classical Mechanics , Applied Mechanics , Strength of Materials , and Physics fundamentals . Human Body Modeling: Experience with Human Body Model (HBM) simulations. Scripting & AI Tools: Familiarity with scripting and the application of AI tools in the analysis process. Materials Expertise: Knowledge of Metals and Composite parts , including failure analysis techniques. Cross-Functional Collaboration: Ability to effectively collaborate with cross functional performance requirements teams. Design & Presentation: Ability to contribute to design proposals and deliver clear and concise presentations . Professional Attributes: Demonstrated responsibility , ownership , and a strong learning aptitude . Communication Skills: Excellent communication skills , both written and verbal. Logical Reasoning: Strong logical reasoning abilities. What We Offer Salary:

Material Planner -Exports (IRF)

RLE India Private Limited•

Chennai

•Full-time

Material Planner - Exports (IRF) Job Summary We are seeking a highly motivated and experienced Material Planner to join our team in Chennai. This role will focus on export-related material planning within the automotive industry. The ideal candidate will possess a strong understanding of material planning principles and a proven ability to manage complex supply chains. Key Responsibilities The Material Planner – Exports (IRF) will be responsible for ensuring the efficient and timely flow of materials required for export operations. This includes managing the planning process, coordinating with various stakeholders, and proactively addressing potential supply chain disruptions. Required Skills & Qualifications Education: A Graduate in Engineering is required. Experience: 3-5 years of experience in material planning or a related field is expected. This level of experience indicates a proficiency in handling routine tasks with minimal supervision and a growing understanding of complex planning scenarios. Serial Life Management: Demonstrated ability to manage materials throughout their lifecycle, from initial procurement to eventual obsolescence, ensuring proper tracking and disposition. Design Change Management: Experience in managing and implementing design changes to materials, ensuring minimal disruption to production and export schedules. Supply Chain Knowledge: A comprehensive understanding of supply chain principles, including procurement, logistics, and inventory management. Supply Chain Flow Management: Ability to analyze and optimize the flow of materials within the supply chain, identifying and resolving bottlenecks to ensure efficient operations. Packaging & Quality Knowledge: Familiarity with packaging requirements and quality control procedures to ensure materials meet export standards. Team Player: Ability to collaborate effectively with cross-functional teams to achieve common goals. Time Oriented: Strong organizational skills and the ability to prioritize tasks to meet deadlines. Leadership: Demonstrated leadership potential, with the ability to motivate and guide others. Intercultural Awareness: Sensitivity to cultural differences and the ability to communicate effectively with individuals from diverse backgrounds. Synthesis Oriented: Ability to analyze complex information and synthesize it into actionable plans. Facilitator: Skill in facilitating discussions and reaching consensus among stakeholders. What We Offer Salary: Not specified.

Quality Data Analyst – Electrical Hardware EngineeringWarranty Analytics | KPI Automation | Design Assessment | AI Adoption

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our Electrical Hardware Engineering team. This role will focus on Warranty Analytics, KPI Automation, Design Assessment, and the adoption of AI within our quality processes. The ideal candidate will possess a strong analytical background and a passion for leveraging data to drive improvements in product quality and operational efficiency. This is an onsite position. Key Responsibilities The Quality Data Analyst will be responsible for a range of tasks including: Performing Data Analysis to identify trends and patterns in warranty data, product performance, and manufacturing processes. Developing and maintaining KPI Reporting dashboards to track key quality metrics and provide actionable insights to stakeholders. Automating KPI generation and reporting processes to improve efficiency and accuracy. Conducting Root-Cause Analysis of quality issues and collaborating with engineering teams to implement effective Corrective Action Management plans. Utilizing Data Mining techniques to uncover hidden patterns and insights within large datasets. Applying Statistical Analysis methods to evaluate product performance and identify areas for improvement. Leveraging AI-Assisted Analytics and Generative AI to enhance data analysis capabilities and identify potential quality risks. Implementing Process Optimization strategies to streamline quality control processes and improve overall efficiency. Required Skills & Qualifications To be successful in this role, candidates must possess the following skills and qualifications: A Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline. 5-10 years of experience in a data analysis role, preferably within the automotive or technology industry. This level of experience indicates a proven ability to independently manage complex data analysis projects and deliver impactful insights. Data Analysis : A strong foundation in data analysis techniques, including data cleaning, transformation, and exploration. Data Visualization : Proficiency in creating compelling and informative data visualizations to communicate insights effectively. Dashboarding : Experience in designing and developing interactive dashboards using tools such as Power BI . KPI Reporting : Ability to define, track, and report on key performance indicators ( KPIs ) to measure quality performance. Data Storytelling : Skill in translating complex data into clear and concise narratives that resonate with stakeholders. Quality Tools : Familiarity with various quality tools and methodologies, such as Lean and Six Sigma . Issue Management : Experience in identifying, tracking, and resolving quality issues in a timely and effective manner. Root-Cause Analysis : Ability to conduct thorough root-cause analyses to identify the underlying causes of quality problems. Corrective Action Management : Experience in developing and implementing corrective action plans to prevent recurrence of quality issues. Process Optimization : Ability to identify and implement process improvements to enhance quality control processes. Power BI : Proficiency in using Power BI to create interactive dashboards and reports. Excel Analytics : Advanced skills in Excel for data analysis and reporting. SQL : Strong proficiency in SQL for querying and manipulating data. Python : Experience using Python for data analysis and automation. Databricks : Familiarity with Databricks for big data processing and analysis. Power Automate : Experience using Power Automate for automating data-related tasks. Warranty Data Analytics : Experience analyzing warranty data to identify trends and patterns. Cost Trend Analysis : Ability to analyze cost trends to identify opportunities for cost savings. KPI Automation : Experience automating KPI generation and reporting processes. Multi-Source Data Integration : Ability to integrate data from multiple sources into a unified view. AI-Assisted Analytics : Experience leveraging AI to enhance data analysis capabilities. Predictive Quality : Ability to use data to predict potential quality issues. Anomaly Detection : Skill in identifying unusual patterns or outliers in data. Generative AI : Familiarity with Generative AI techniques for data analysis and insights. Process Automation : Experience automating manual processes to improve efficiency. Data Mining : Ability to extract valuable insights from large datasets. Statistical Analysis : Proficiency in applying statistical methods to analyze data. Quality Metrics : Understanding of key quality metrics and their application. Data Definitions : Ability to define clear and consistent data definitions. What We Offer We offer a competitive salary of .

Quality Data Analyst – Electrical Hardware Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our Electrical Hardware Engineering, Warranty Analytics & Quality Automation team. This role will be instrumental in leveraging data to drive quality improvements, identify trends, and ensure the reliability of our products. The ideal candidate will possess a strong analytical background, a passion for data-driven decision-making, and a commitment to continuous improvement within the automotive and technology industries. Key Responsibilities The Quality Data Analyst will be responsible for a range of tasks related to data analysis, reporting, and process improvement. This includes conducting in-depth analysis of warranty data, identifying cost trends, and developing automated reporting solutions. The role will also involve collaborating with cross-functional teams to implement corrective actions and preventative measures to enhance product quality and reliability. Required Skills & Qualifications To be successful in this role, candidates must possess a combination of technical skills, analytical abilities, and a strong understanding of quality methodologies. Specific requirements include: Analytical Skills: Demonstrated ability to analyze complex data sets, identify patterns, and draw meaningful conclusions. Problem-Solving Skills: Proven ability to approach complex problems systematically, identify root causes, and develop effective solutions. Data Analysis: Proficiency in data analysis techniques, including statistical analysis and data mining. Data Visualization: Ability to create clear and compelling data visualizations to communicate insights effectively. Dashboarding: Experience in designing and developing interactive dashboards to monitor key performance indicators (KPIs). KPI Reporting: Ability to generate regular reports on KPIs and present findings to stakeholders. Data Storytelling: Ability to translate data into a narrative that is easy to understand and actionable. SQL: Strong proficiency in SQL for data extraction, manipulation, and analysis. Python: Experience using Python for data analysis and automation. Databricks: Familiarity with Databricks for large-scale data processing and analytics. Power Automate: Experience with Power Automate for automating data-related tasks and workflows. Warranty Data Analytics: Expertise in analyzing warranty data to identify trends and opportunities for improvement. Cost Trend Analysis: Ability to analyze cost data to identify trends and potential cost savings. KPI Automation: Experience in automating the generation and distribution of KPIs. Multi-Source Data Integration: Ability to integrate data from multiple sources into a unified view. AI-Assisted Analytics: Experience leveraging AI to enhance data analysis and predictive modeling. Predictive Quality: Knowledge of predictive quality techniques to anticipate and prevent quality issues. Anomaly Detection: Ability to identify unusual patterns or outliers in data that may indicate quality problems. Generative AI: Familiarity with Generative AI techniques for data analysis and problem-solving. Issue Management: Experience in tracking and resolving quality issues. Root-Cause Analysis: Proficiency in conducting root-cause analysis to identify the underlying causes of quality problems. Corrective Action Management: Ability to develop and implement effective corrective actions to prevent recurrence of quality issues. DFMEA: Understanding of DFMEA (Design Failure Mode and Effects Analysis) principles. DRBFM: Understanding of DRBFM (Design Review Based on Failure Mode) principles. APQP: Understanding of APQP (Advanced Product Quality Planning) principles. Statistical Tools: Proficiency in using various statistical tools for data analysis and quality improvement. Structured Problem Solving: Ability to apply structured problem-solving methodologies to address quality challenges. Power BI: Proficiency in Power BI for data visualization and reporting. Excel Analytics: Strong Excel skills for data analysis and reporting. Process Optimization: Ability to identify and implement process improvements to enhance quality and efficiency. Six Sigma: Knowledge of Six Sigma methodologies for process improvement. Quality Tools: Familiarity with various quality tools and techniques. Lean: Understanding of Lean principles for waste reduction and process improvement. Education: A Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline is required. Experience: The ideal candidate will have 5-10 years of experience in a related field, demonstrating a strong track record of success in data analysis and quality improvement. This level of experience is expected to provide a solid foundation for independent work and leadership within a team. What We Offer Salary:

DCL Quality

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly motivated and experienced DCL Quality professional to join our team in the Automotive industry. This is an onsite position requiring a blend of technical expertise and strong communication skills. The ideal candidate will possess a strong understanding of design and quality processes within a manufacturing environment. Key Responsibilities This role will be responsible for ensuring the quality and integrity of designs and components throughout the development lifecycle. Specific responsibilities will include analyzing designs, identifying potential issues, and collaborating with engineering teams to implement effective solutions. Required Skills & Qualifications Bachelor’s degree in mechanical engineering or a related field. Advanced degree preferred, demonstrating a commitment to advanced knowledge and expertise in the field. CAD proficiency is essential, with experience in utilizing CAD software for design analysis and validation. TCE experience is required, demonstrating a strong understanding of tolerance stack-up and its impact on product quality. PLM experience is necessary, with a proven ability to manage and track design changes within a PLM system. CN sweeps expertise is needed, with a solid understanding of their application in design and manufacturing. Ability to create Suspension kinematics mechanism designs, demonstrating a strong understanding of mechanical principles. Motion simulation skills are required, with the ability to use simulation tools to analyze and optimize designs. Problem-solving skills are critical, with a demonstrated ability to identify and resolve complex design issues. Communication skills are essential, with the ability to clearly and effectively communicate technical information to both technical and non-technical audiences. Teamwork skills are vital, with a proven ability to collaborate effectively with cross-functional teams. Analytical Skills are required, with the ability to analyze data and draw meaningful conclusions. Strategic thinking skills are needed, with the ability to anticipate future challenges and develop proactive solutions. GD&T knowledge is essential, with a thorough understanding of geometric dimensioning and tolerancing principles. Clash and Clearance analysis experience is required, with the ability to identify and resolve potential interference issues. Packaging expertise is needed, with a strong understanding of how to optimize designs for manufacturability and assembly. Experience Required: 6 - 9 years of experience in a related field. This level of experience indicates a seasoned professional capable of independent work and mentoring junior team members. Expectation is for a high level of proficiency and the ability to lead projects and initiatives. What We Offer Salary: Not provided.

CAE Analyst

RLE India Private Limited•

Chennai

•Full-time

CAE Analyst Job Description Job Summary We are seeking a skilled and experienced CAE Analyst to join our team in Chennai. This role is crucial for supporting our Automotive / Mechanical Engineering initiatives, ensuring the quality and durability of our components and systems. Key Responsibilities The CAE Analyst will be responsible for performing a wide range of CAE simulations and analyses to support product development and validation. This includes, but is not limited to, conducting structural analysis , stress analysis , and fatigue life prediction . The role will also involve root cause analysis and failure analysis to identify and resolve potential issues. The analyst will work closely with design and validation teams to ensure that designs meet performance and durability requirements. Required Skills & Qualifications The ideal candidate will possess a strong foundation in Mechanical Engineering and a proven ability to apply CAE principles to solve real-world engineering problems. A B.E / B.Tech / M.E / M.Tech degree is required. Non-linear FE analysis: Proficiency in performing advanced finite element analyses, including non-linear simulations to accurately predict component behavior under complex loading conditions. Abaqus: Demonstrated experience using Abaqus for conducting FE simulations. FE model building: Ability to create accurate and efficient FE models representing complex geometries and boundary conditions. Meshing: Expertise in generating high-quality meshes using industry-standard tools. HyperMesh: Experience utilizing HyperMesh for efficient mesh generation and model preparation. ANSA: Familiarity with ANSA for pre- and post-processing of FE models. Fatigue life prediction: Ability to perform fatigue life prediction using established methodologies and software. FEMFAT: Experience with FEMFAT for fatigue analysis and damage assessment. Structural analysis: A strong understanding of structural analysis principles and their application to automotive components. Stress analysis: Ability to perform detailed stress analysis to identify areas of high stress concentration and potential failure. Material modeling: Knowledge of material modeling techniques and their impact on simulation results. Contact definitions: Ability to accurately define and implement contact definitions in FE models. Reliability assessments: Experience in performing reliability assessments to evaluate the long-term performance of components. Durability assessments: Ability to conduct durability assessments to ensure components can withstand expected usage conditions. Root cause analysis: Proven ability to perform root cause analysis to identify the underlying causes of failures. Failure analysis: Experience in conducting failure analysis to determine the mechanisms of failure. Automotive engineering: A solid understanding of Automotive engineering principles and practices. Quality processes: Familiarity with quality processes and their application to product development. Robust design methodologies: Knowledge of robust design methodologies to create designs that are insensitive to variations in manufacturing and operating conditions. Manufacturing best practices: Understanding of manufacturing best practices and their impact on component performance. Transmission & driveline systems: Familiarity with Transmission & driveline systems and their components. Gears, Shafts, Clutches, Differentials, Propshafts, Half-shafts, Bearings: Knowledge of the design and analysis of these key components. HyperWorks: Experience with HyperWorks for CAE simulation and analysis. Fatigue life/Damage assessment: Ability to perform fatigue life/Damage assessment to predict component lifespan. Boundary conditions: Ability to accurately define and apply appropriate boundary conditions in FE models. Dynamic loading scenarios: Experience in simulating dynamic loading scenarios to evaluate component response to transient loads. Gear strength: Ability to assess gear strength and durability. Shaft durability: Ability to assess shaft durability under various loading conditions. Road load data: Experience in utilizing road load data for simulation. Simulation load cases: Ability to develop and apply appropriate simulation load cases . Physical test data: Ability to correlate simulation results with physical test data . Refine models: Ability to refine models based on simulation results and experimental data. Material properties: Understanding of material properties and their impact on simulation results. Manufacturing processes: Familiarity with manufacturing processes such as Forging, Casting, and Heat treatment . Component durability: Ability to assess component durability under various operating conditions. CAE simulation tools: Proficiency in using various CAE simulation tools . Customer usage profiles: Ability to incorporate customer usage profiles into simulation models. Duty cycles: Ability to define and apply appropriate duty cycles in simulations. Design robustness: Ability to assess and improve design robustness . DFMEA: Familiarity with DFMEA (Design Failure Mode and Effects Analysis). DVP&R: Understanding of DVP&R (Design Verification Plan and Release). Experience Required: The role requires 4 - 9 years of relevant experience in CAE analysis, preferably within the Automotive or Mechanical Engineering industry. Candidates with a strong track record of solving complex engineering problems and delivering high-quality results are highly encouraged to apply. What We Offer Salary: ₹10 LPA - ₹12 LPA

Test Architect – Functional, Automation & Performance Testing

SACHA Engineering•

Bengaluru

+4 More

Other Locations4 cities

Mumbai

Pune

Chennai

Hyderabad

•full time

Job Summary We are seeking a highly skilled and experienced Test Architect to join our team. This role will focus on developing and implementing comprehensive testing strategies encompassing functional, automation, and performance testing. The ideal candidate will possess a strong understanding of quality engineering principles and a proven ability to design and execute effective testing frameworks. Key Responsibilities The Test Architect will be responsible for the design, implementation, and maintenance of testing strategies and frameworks. This includes defining quality gates, establishing metrics, and ensuring adherence to best practices. The role will also involve collaboration with cross-functional teams to ensure the delivery of high-quality software releases. Required Skills & Qualifications Test Strategy: Demonstrated ability to develop and execute comprehensive test strategies aligned with business objectives and project requirements. Quality Engineering Architecture: Expertise in designing and implementing quality engineering architectures that support scalable and reliable testing processes. Functional Testing: Proficient in functional testing methodologies to ensure software meets specified requirements. Regression Testing: Experience in designing and executing regression testing suites to identify and prevent regressions. Automation Testing: Strong skills in automation testing, including the ability to design, develop, and maintain automated test scripts. API Testing: Knowledge of API testing techniques to validate the functionality and performance of APIs. Integration Testing: Experience in integration testing to ensure seamless integration between different software components. Performance Testing: Expertise in performance testing methodologies to identify and address performance bottlenecks. Non-Functional Testing: Understanding of non-functional testing aspects, including security, usability, and reliability. CI/CD Integration: Experience integrating testing processes into CI/CD pipelines. Performance Engineering: Ability to apply performance engineering principles to optimize software performance. Quality Gates: Ability to define and implement quality gates to ensure release quality. Metrics & Reporting: Experience in defining and tracking key testing metrics and generating comprehensive reports. Best Practices: Deep understanding of software testing best practices. Automation Frameworks: Experience with various Automation Frameworks . Reusability & Maintainability: Ability to design test automation frameworks with a focus on reusability and maintainability. Service Virtualization: Knowledge of Service Virtualization techniques for creating realistic testing environments. AI-Assisted Testing: Familiarity with AI-Assisted Testing concepts and tools. QE Practices: Strong understanding of QE Practices . Defect Prevention: Ability to identify and implement strategies for defect prevention. Release Quality: Commitment to ensuring high-quality software releases. Analytical Skills: Strong analytical skills to analyze test results and identify root causes of defects. Problem-Solving Skills: Excellent problem-solving skills to effectively troubleshoot and resolve testing issues. Communication Skills: Effective communication skills to clearly and concisely communicate testing results and recommendations. Test Architect: Demonstrated experience and expertise as a Test Architect . Experience Required: 9 - 16 years of experience in software testing, with a focus on test architecture and design. This level of seniority requires a proven track record of leading testing initiatives and mentoring junior team members. What We Offer Salary: 30 LPA

Vehicle Performance Test Engineer

RLE India Private Limited•

Remote

•full time

Job Summary We are seeking a highly motivated and experienced Vehicle Performance Test Engineer to join our team. This role will focus on conducting and analyzing vehicle performance tests, ensuring the quality and performance of our vehicles. Key Responsibilities The Vehicle Performance Test Engineer will be responsible for planning, executing, and documenting vehicle performance tests. This includes conducting various tests related to fuel economy, emissions, vehicle drivability, and transmission performance. The engineer will also be responsible for analyzing test data, identifying areas for improvement, and collaborating with engineering teams to implement solutions. Required Skills & Qualifications Bachelor’s degree in mechanical or Automobile Engineering. 6-8 years of experience in vehicle performance testing. This level of experience indicates a seasoned professional capable of independently planning and executing complex test programs, analyzing results, and contributing to vehicle development. Analytical Skills: Demonstrated ability to analyze complex data and draw meaningful conclusions. Problem-Solving Skills: Proven ability to identify and resolve technical issues related to vehicle performance. Communication Skills: Excellent written and verbal communication skills, with the ability to clearly and concisely communicate technical information to both technical and non-technical audiences. Teamwork: Ability to work effectively as part of a team, collaborating with engineers and other stakeholders to achieve common goals. Data Analysis: Proficiency in data analysis techniques and methodologies. Excel: Advanced proficiency in Excel for data manipulation, analysis, and reporting. MDA: Experience with MDA (Motor Development Analyzer) for vehicle performance analysis. Power BI: Experience using Power BI for data visualization and reporting. Google Slides and Google Sheets: Proficiency in using Google Slides and Google Sheets for presentations and data management. PowerPoint: Proficiency in using PowerPoint for presentations. Vehicle Testing: Comprehensive understanding of vehicle testing methodologies and procedures. DVP Tests: Experience with DVP (Development Verification Plan) tests. Vehicle Coast Down: Expertise in conducting and analyzing Vehicle Coast Down tests. Fuel Economy: Deep understanding of Fuel Economy testing and analysis. Gradeability: Experience in evaluating Gradeability performance. Emission Testing: Knowledge of Emission Testing procedures and regulations. TA & COP: Familiarity with TA & COP (Transmission Application and Calibration Optimization Process). Subjective Assessment: Ability to conduct and interpret Subjective Assessment of vehicle performance. Vehicle Drivability: Experience in evaluating Vehicle Drivability characteristics. Gear Shift Quality: Ability to assess and analyze Gear Shift Quality . Manual Transmission: Understanding of Manual Transmission systems and testing. Automatic Transmission: Understanding of Automatic Transmission systems and testing. Benchmark Vehicle Testing: Experience in conducting Benchmark Vehicle Testing . Root Cause Analysis: Ability to perform Root Cause Analysis to identify and resolve performance issues. Benchmarking: Experience in conducting Benchmarking studies. Data Seeking: Ability to effectively Data Seeking to support analysis and decision-making. Technical Discussions: Ability to participate in and lead Technical Discussions . Calibration: Experience with vehicle Calibration processes. Application Management: Experience in Application Management related to vehicle testing. V Box: Experience using V Box for vehicle performance measurement. Ipetronic: Experience using Ipetronic for engine testing and analysis. L350 Aqua Sensor: Experience using L350 Aqua Sensor for environmental testing. CAN Analyser: Experience using CAN Analyser for vehicle communication analysis. DFL: Familiarity with DFL (Data Flash Loader). INCA: Experience using INCA (IN Control) for ECU calibration and diagnostics. ETAS: Familiarity with ETAS (Electrical Transport and Automotive Systems) products and technologies. What We Offer Salary: