Lean Jobs in Chennai

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:

Scrum Master

RLE India Private Limited•

Pune

•full time

Job Summary We are seeking a skilled and experienced Scrum Master to join our dynamic team in Pune. This role is crucial for ensuring the successful delivery of high-quality software solutions through the effective application of Agile principles and practices. The ideal candidate will possess a strong understanding of the software development lifecycle and a proven ability to facilitate Scrum events and remove impediments for development teams. Key Responsibilities The Scrum Master will be responsible for guiding and coaching development teams on the use of Scrum , ensuring they adhere to Agile values and principles. This includes facilitating Scrum ceremonies, such as sprint planning, daily Scrum , sprint review, and sprint retrospective. The role also involves identifying and removing impediments that hinder the team's progress, fostering a collaborative and self-organizing environment. Required Skills & Qualifications Understanding of Software Development Lifecycle (SDLC): A comprehensive understanding of the various phases of the software development lifecycle, from inception to deployment and maintenance. Agile Engineering Practices: Demonstrated proficiency in Agile methodologies, particularly Scrum , and the ability to coach teams on their effective implementation. Common Engineering Workflows: Familiarity with standard engineering workflows, including version control, code review, and continuous integration. Web Application Technologies: Knowledge of technologies used in web application development, including Angular . Mobile Application Technologies: Understanding of technologies used in mobile application development. Desktop Application Technologies: Understanding of technologies used in desktop application development, including C# , .NET , and WPF . Ability to Work with Technical Leads: Proven ability to collaborate effectively with technical leads to ensure alignment on technical direction and execution. DevOps Tools & Workflows: Experience with DevOps tools and workflows, including CI/CD . Backlog Tools: Proficiency in using Backlog tools such as Jira and Azure Boards to manage product and sprint backlogs. Communication Skills: Excellent verbal and written communication skills, with the ability to clearly and concisely convey technical information to both technical and non-technical audiences. English: Fluency in English, both written and spoken. Estimation, Dependencies, Risks: Ability to facilitate discussions and guide teams in estimating tasks, identifying dependencies, and assessing risks. Metrics: Understanding of key Scrum metrics, including Velocity , Burndown , and Flow Efficiency . Scrum Artifacts: Deep understanding of Scrum artifacts, including the Product Backlog , Sprint Backlog , and Increment . Technical Execution & Craftsmanship: Appreciation for Technical Craftsmanship principles, Clean Code , and Maintainability . Testing Approach & System Stability: Understanding of testing approaches and their impact on System Stability . System Integration Concepts: Knowledge of API and Cloud concepts and System Integration concepts. Experience Required: The ideal candidate will have 4-6 years of experience in a related role, demonstrating a solid foundation in software development and Agile practices. This level of experience is expected to provide a strong understanding of team dynamics and the ability to effectively facilitate Scrum events and remove impediments. What We Offer Salary:

CAE Modeler

SACHA Engineering•

Chennai

•full time

Job Summary We are seeking an experienced CAE Modeler to join our team in Chennai. As a CAE Modeler, you will play a critical role in the design and development of automotive products, utilizing advanced computer-aided engineering (CAE) tools to simulate and analyze the behavior of complex systems. This is an excellent opportunity to work on challenging projects, collaborate with cross-functional teams, and contribute to the development of innovative solutions. The ideal candidate will have a strong foundation in mechanical engineering, materials science, and computer-aided design (CAD). You will be responsible for creating detailed CAE models, performing simulations, and analyzing results to inform design decisions. Your expertise in CAE tools, such as Autodesk Moldflow, ANSYS, Abaqus, Nastran, and HyperMesh, will be essential in driving the development of high-quality products. Key Responsibilities Create detailed CAE models for simulation and analysis of complex systems, including structural, thermal, and multi-physics problems. Perform simulations using Autodesk Moldflow, ANSYS, Abaqus, Nastran, and HyperMesh, and analyze results to inform design decisions. Develop and maintain CAE models, including meshing and CAD cleanup, to ensure accuracy and efficiency. Apply materials and process fundamentals to CAE modeling and simulation. Utilize Python scripting for CAE automation, reporting, and data visualization. Collaborate with cross-functional teams to integrate CAE results into the design and development process. Required Skills & Qualifications Bachelor's degree in Mechanical Engineering, Plastics, Automotive, Aerospace, Electrical & Electronics, or a related field. Master's degree (ME/MTech) in a relevant field, such as CAD/CAE, Design, Manufacturing, Computer Science, Artificial Intelligence/Machine Learning, or Electrical & Computer Engineering, is a plus. 2+ years of experience in CAE modeling and simulation, preferably in the automotive industry. Proficiency in Autodesk Moldflow, Structural CAE/FEA (ANSYS/Abaqus/Nastran/HyperMesh), meshing & CAD cleanup. Strong understanding of materials and process fundamentals. Experience with Python scripting for CAE automation, reporting, and data visualization. Knowledge of data visualization techniques and tools. What We Offer We offer a dynamic and collaborative work environment in Chennai, with opportunities for professional growth and development. As an onsite role, you will be working closely with our team to drive innovation and excellence in the automotive industry. job ID : CJ2025-45002 (0015)