Bi Tools Jobs

GCP Data Engineer

SACHA Engineering•

Chennai

•Full-time

Job Summary We are seeking a skilled and experienced GCP Data Engineer to join our growing team in Chennai. This role is critical to building and maintaining our data infrastructure, ensuring data quality, and enabling data-driven decision-making across the organization. The ideal candidate will possess a strong foundation in data engineering principles and a proven ability to work with cloud-based technologies, specifically the GCP platform. Key Responsibilities The GCP Data Engineer will be responsible for the following: Designing, building, and maintaining robust and scalable data pipelines using ETL processes. Developing and implementing data quality checks and validation procedures to ensure data accuracy and reliability. Ingesting data from various sources, including APIs and databases, into our GCP environment. Performing Data Mining and Data Analytics to identify trends and insights. Collaborating with cross-functional teams to understand data requirements and deliver effective data solutions. Utilizing Git version control for code management and collaboration. Developing and maintaining RESTful APIs for data access and integration. Required Skills & Qualifications To be successful in this role, candidates must possess the following skills and qualifications: Proficiency in Data Engineering principles and practices. Strong experience with BI Tools for data visualization and reporting. Expertise in SQL for data querying and manipulation. Solid programming skills in Python for data processing and automation. Experience with API Development , including designing and implementing RESTful APIs . Hands-on experience with GCP services for data storage, processing, and analytics. Familiarity with Data Integration techniques and tools. Understanding of Data Quality principles and methodologies. Experience with Data Ingestion from various sources. Proficiency in using Git version control for collaborative code management. Experience Required: 5 - 10 years of relevant experience in data engineering, demonstrating a strong track record of building and maintaining data pipelines and working with cloud technologies. This level of experience indicates a senior-level role requiring independent problem-solving and the ability to mentor junior team members. What We Offer Salary:

Project Management

SACHA Engineering•

Chennai

•Full-time

Project Management Job Description Job Summary We are seeking a skilled and motivated Project Management professional to join our team in Chennai. This role will be instrumental in managing and coordinating various projects within our IT / Technology environment. Key Responsibilities The Project Management role will involve a range of responsibilities focused on ensuring projects are completed efficiently and effectively. This includes utilizing Project Management Tools and Project Management Techniques to plan, execute, and monitor project progress. The successful candidate will be expected to adhere to Industry Standards and contribute to a positive project outcome. Required Skills & Qualifications Project Management Tools: Proficiency in utilizing various Project Management Tools to facilitate project planning, task assignment, and progress tracking. Project Management Techniques: A strong understanding of Project Management Techniques , including but not limited to Agile, Waterfall, or hybrid methodologies, to effectively manage project scope, timelines, and resources. Industry Standards: Familiarity with relevant Industry Standards to ensure project deliverables meet quality and compliance requirements. Automotive-Specific Terminology: A working knowledge of Automotive-Specific Terminology is highly desirable, allowing for effective communication and understanding within the context of our projects. Product Development Lifecycles: Understanding of Product Development Lifecycles to ensure alignment with overall business objectives. Data Analysis Tools: Ability to leverage Data Analysis Tools to extract meaningful insights from project data, identify trends, and inform decision-making. Excel: Advanced proficiency in Excel for data manipulation, analysis, and reporting. VBA: Experience with VBA for automating tasks and enhancing Excel functionality. PowerBI: Ability to create and utilize PowerBI dashboards to visualize project data and communicate key performance indicators. Organizational Skills: Exceptional Organizational Skills to manage multiple tasks, prioritize effectively, and maintain meticulous project documentation. Analytical Skills: Strong Analytical Skills to assess project risks, identify potential issues, and develop effective mitigation strategies. Problem-Solving Skills: Demonstrated Problem-Solving Skills to address challenges proactively and implement creative solutions. Written Communication Skills: Excellent Written Communication Skills to prepare clear and concise project documentation, reports, and correspondence. Verbal Communication Skills: Effective Verbal Communication Skills to communicate project status, updates, and concerns to stakeholders. PowerPoint Skills: Proficiency in PowerPoint to create compelling presentations for project updates and stakeholder meetings. Experience Required: We are seeking candidates with 1 - 5 years of experience in a related field. This level of experience indicates a foundational understanding of project management principles and the ability to contribute effectively to a team. The expectation is that candidates will be able to work independently on assigned tasks and contribute to the overall success of the project. What We Offer Salary: [Salary Information Not Provided]

Python Data Analytics

SACHA Engineering•

Chennai

•Full-time

Job Summary We are seeking a skilled Python Data Analytics professional to join our team in Chennai. This role offers an exciting opportunity to contribute to a dynamic environment within the IT / Technology industry. Key Responsibilities This role will involve a range of responsibilities centered around data analysis and reporting, leveraging Python and related technologies to extract meaningful insights from complex datasets. The successful candidate will be expected to demonstrate a strong ability to translate data into actionable recommendations. Required Skills & Qualifications Python : Proficiency in Python programming is essential, including experience in developing and implementing data analysis scripts and algorithms. Data Analytics : A strong foundation in Data Analytics principles and techniques, with the ability to apply these to real-world business problems. Big Data Query : Experience with Big Data Query techniques and tools to efficiently process and analyze large datasets. GCP : Familiarity with GCP (Google Cloud Platform) for data storage, processing, and analysis. Github : Experience using Github for version control and collaborative development. Pandas : Expertise in using Pandas for data manipulation and analysis. NumPy : Proficiency in utilizing NumPy for numerical computations and array processing. SciPy : Knowledge of SciPy for scientific computing and statistical analysis. Dask : Experience with Dask for parallel computing and scaling data analysis tasks. Hadoop : Understanding of Hadoop ecosystem for distributed data storage and processing. Hive : Experience with Hive for querying and analyzing data stored in Hadoop . Spark : Proficiency in using Spark for fast and scalable data processing. Data Retrieval : Ability to retrieve data from various sources and formats. Data Processing : Strong skills in data cleaning, transformation, and preparation for analysis. RESTful Web APIs : Understanding of RESTful Web APIs for data integration and exchange. Data Sources : Ability to connect to and extract data from diverse Data Sources . Windows & Linux : Comfortable working in both Windows and Linux environments. Written Communication Skills : Excellent Written Communication Skills for creating clear and concise reports and documentation. Verbal Communication Skills : Strong Verbal Communication Skills for presenting findings and collaborating with stakeholders. Organizational Skills : Demonstrated Organizational Skills for managing multiple tasks and priorities effectively. Attention to Detail : A meticulous Attention to Detail to ensure data accuracy and integrity. Multi-tasking Skills : Ability to effectively manage and prioritize multiple tasks simultaneously. Reporting Tools : Experience with various Reporting Tools for creating insightful visualizations and dashboards. Metrics : Understanding of key performance indicators ( Metrics ) and their application in data analysis. Visualizations : Ability to create compelling Visualizations to communicate data insights effectively. Software Traceability : Knowledge of Software Traceability principles and practices. Documentation : Ability to create comprehensive and accurate Documentation for data analysis processes and results. Experience Required: The ideal candidate will possess 4 - 8 years of relevant experience in a data analytics role, demonstrating a proven ability to deliver impactful insights and solve complex business problems. This level of experience indicates a level of seniority requiring independent work and mentorship capabilities. What We Offer Salary:

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:

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:

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:

Virtual Analysis Engineer Safety Bio

RLE India Private Limited•

Pune

+1 More

Other Locations1 cities

Chennai

•full time

Job Summary We are seeking a highly skilled and motivated Virtual Analysis Engineer Safety Bio to join our team. This role will focus on virtual analysis and simulation to support safety and bioengineering initiatives within the automotive industry. The ideal candidate will possess a strong analytical background and experience with industry-standard CAE tools. Key Responsibilities The Virtual Analysis Engineer Safety Bio will be responsible for performing and interpreting virtual analyses, contributing to the development of safety systems, and collaborating with cross-functional teams to ensure the safety and performance of our vehicles. This includes conducting Failure Analysis , utilizing Human Body Model (HBM) Simulations , and contributing to Vehicle Crashworthiness assessments. Required Skills & Qualifications Educational Background: A B.E , B.Tech (Mechanical, Automobile), M.E , or M.Tech degree is required. Analytical Skills: Demonstrated ability to analyze complex data, identify trends, and draw meaningful conclusions. This includes a strong foundation in Classical Mechanics and Applied Mechanics . Problem-Solving Skills: Proven ability to identify, analyze, and solve complex engineering problems related to safety and bioengineering. 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. Software Proficiency: Demonstrated proficiency in the use of industry-standard CAE software, including PRIMER , ANSA , and LS-DYNA . Scripting and Programming: Experience with Linux Scripting and Python , including the use of Jupyter Notebook for data analysis and visualization. AI Tools: Familiarity with AI Tools and their application to engineering problems. Safety Systems Expertise: A solid understanding of Occupant-Restraint-System Development , including experience with Single-Stage Airbags and Seatbelts with Constant Force Retractors . Experience: A minimum of 6 - 9 years of relevant experience in a similar role is expected. This level of experience indicates a seasoned professional capable of independent work and mentorship. What We Offer Salary: This position is onsite .

CAM Engineer

SACHA Engineering•

Chennai

•full time

Job Summary We are seeking a skilled and detail-oriented professional to join our manufacturing team in Chennai. This role will be instrumental in ensuring the precision and efficiency of our machining operations. Key Responsibilities This position involves a range of responsibilities centered around the operation and programming of CNC machines, ensuring adherence to strict quality standards and contributing to continuous process improvement. Required Skills & Qualifications Educational Background: A degree in Mechanical or Automobile Engineering is required. CAD Proficiency: Demonstrated ability to work with CAD software to interpret and utilize engineering drawings and 3D CAD Models . Blueprint Analysis: Strong skills in Blueprint Analysis to accurately understand and implement design specifications. Engineering Drawings: Ability to interpret and utilize Engineering Drawings effectively. CNC Programming: Expertise in CNC Programming to create and optimize machining programs. CNC Machine Operation: Proficient in the operation of CNC machines, ensuring precise execution of programmed tasks. Machine Tools: Comprehensive understanding of Machine Tools and their functionalities. Cutting Tools: Knowledgeable in the selection and application of Cutting Tools for various machining operations. Tebis & Tebis Cam: Proficiency in Tebis and Tebis Cam software for advanced machining operations. Machining Expertise: Experience with both 3 Axis Machining and 5 Axis Machining techniques. Machine Usage: Ability to effectively utilize Machine Usage to achieve desired results. Program Execution: Skill in Program Execution , ensuring accurate and efficient machining processes. Troubleshooting: Strong Troubleshooting skills to identify and resolve issues in machining operations. Process Improvement: Commitment to Process Improvement , seeking opportunities to enhance efficiency and quality. Safety Protocols: Strict adherence to Safety Protocols to maintain a safe working environment. Experience: 4 years of relevant experience are required. The ideal candidate will possess a solid foundation in machining principles and a proven ability to work independently and as part of a team.

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: