Python Jobs in Mumbai

Google Cloud Engineer - SSE

SACHA Engineering•

Bengaluru

+4 More

Other Locations4 cities

Mumbai

Pune

Chennai

Hyderabad

•full time

Job Summary We are seeking a skilled and experienced Google Cloud Engineer - Site Support Engineer (SSE) to join our dynamic IT / Technology team. This is a hybrid role requiring a blend of on-site and remote work. The ideal candidate will possess a strong foundation in cloud technologies, particularly within the Google Cloud Platform , and a proven ability to design, implement, and maintain robust and scalable cloud solutions. Key Responsibilities The Google Cloud Engineer - SSE will be responsible for a range of tasks related to the design, implementation, and maintenance of our Google Cloud infrastructure. This includes ensuring high availability, implementing robust security measures, and proactively identifying and resolving potential issues. The role requires a strong focus on automation and continuous improvement to optimize our cloud environment. Required Skills & Qualifications Education: A Bachelor’s degree in computer science or a related field, or a higher degree, is required. Experience: A minimum of 6-9 years of relevant experience in cloud engineering or a related field is expected. This level of experience indicates a seasoned professional capable of independently managing complex cloud environments and mentoring junior team members. DevOps: Demonstrated proficiency in DevOps principles and practices, with a focus on automation, continuous integration, and continuous delivery. Google Kubernetes Engine (GKE): Extensive experience with GKE , including cluster configuration, scaling, and management. Infrastructure-as-Code: Strong understanding and practical experience with Infrastructure-as-Code methodologies and tools. Terraform: Expertise in using Terraform to provision and manage Google Cloud resources. Deployment Manager: Familiarity with Deployment Manager for automated deployment of Google Cloud applications and infrastructure. CI/CD: Proven ability to design and implement CI/CD pipelines using tools such as Cloud Build , Jenkins , and GitHub Actions . Kubernetes: Deep understanding of Kubernetes concepts, including Deployments , Services , and Ingress . Helm: Experience using Helm for package management and deployment of Kubernetes applications. Programming Languages: Proficiency in at least one or more of the following programming languages: Python , Bash , Go . GitOps: Knowledge of GitOps principles and experience with tools like ArgoCD . Cloud Governance: Understanding of Cloud Governance best practices and experience implementing policies and controls. Cost Management: Ability to monitor and optimize cloud costs. Compliance: Familiarity with compliance requirements and experience implementing security controls. Cloud Migration: Experience with Cloud Migration strategies and execution. System Reliability: A strong focus on System Reliability and the ability to design and implement highly available and resilient systems. High Availability & Redundancy: Experience designing and implementing High Availability and Redundancy solutions. Backup Strategies: Knowledge of effective Backup Strategies and implementation. Proactive Monitoring: Ability to implement Proactive Monitoring solutions to identify and resolve potential issues before they impact users. Process Efficiencies: A commitment to identifying and implementing Process Efficiencies to improve operational efficiency. Analytical Skills: Strong Analytical Skills to troubleshoot complex issues and identify root causes. Problem-Solving Skills: Excellent Problem-Solving Skills to effectively resolve technical challenges. Communication Skills: Exceptional Communication Skills to clearly and concisely communicate technical information to both technical and non-technical audiences. Relationship Building: Ability to build and maintain strong relationships with stakeholders across the organization. Planning & Prioritization: Strong Planning and Prioritization skills to manage multiple tasks and projects effectively. What We Offer Salary: ₹20,00,000 per annum.

Senior Engineer_Loads Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly skilled and motivated Senior Engineer to join our growing team. This role is ideal for a seasoned professional with a strong background in automotive or technology, possessing a blend of analytical expertise and practical engineering experience. The successful candidate will contribute to challenging projects, leveraging their technical skills to solve complex problems and drive innovation. Key Responsibilities While specific responsibilities will evolve with project needs, the Senior Engineer will be expected to contribute to a range of engineering tasks, demonstrating initiative and a commitment to delivering high-quality results. This includes applying engineering principles to analyze and solve problems, documenting findings clearly and concisely, and collaborating effectively with cross-functional teams. Required Skills & Qualifications Education: A PhD , M.E/ M.Tech , or B.E/ B.Tech degree in Automobile , Mechanical , or Design Engineering is required. Experience: 3-5 years of relevant professional experience is expected, demonstrating a solid foundation in engineering principles and practical application. This level of experience indicates the ability to work independently, contribute to team goals, and mentor junior engineers. Software Proficiency: Demonstrated expertise in the following software and tools: Adams/View : Proficient in utilizing Adams/View for multi-body dynamics simulation and analysis. Adams/Car : Experience with Adams/Car for vehicle dynamics simulation and modeling. Insight : Ability to leverage Insight for post-processing and visualization of simulation results. Motion View : Familiarity with Motion View for visualizing and analyzing motion data. Hypergraph : Skilled in using Hypergraph for data analysis and visualization. NASTRAN : Experience with NASTRAN for finite element analysis. MATLAB : Proficient in using MATLAB for numerical computation and simulation. Simulink : Skilled in utilizing Simulink for dynamic system modeling and simulation. Adams Command Language : Ability to use Adams Command Language for scripting and automation. Python : Programming skills in Python for data analysis and automation. Linux : Familiarity with Linux operating systems for engineering tasks. Engineering Knowledge: Strong understanding of the following engineering principles: K&C : Knowledge of Kinematics and Compliance analysis. vRLDA : Experience with virtual reality load data analysis. Durability Loads Calculations : Ability to perform durability load calculations. Vehicle Dynamics : Solid understanding of vehicle dynamics principles. Analytical & Problem-Solving Skills: Exceptional Analytical Skills and Problem-Solving Skills to identify, analyze, and resolve complex engineering challenges. Communication & Interpersonal Skills: Excellent Communication Skills , both written and verbal, to effectively communicate technical information to a variety of audiences. Organizational & Management Skills: Strong Organization and Planning skills to manage multiple tasks and prioritize effectively. Program Management experience is a plus. Documentation Skills: Ability to produce clear and concise Technical Writing for reports and documentation. Presentation Skills: Ability to deliver engaging and informative Presentations . Software Suite: Proficiency in MS Office suite, including Excel , PowerPoint , and Word . What We Offer Salary:

Virtual Analysis Engineer Safety Biomechanics

RLE India Private Limited•

Chennai

•full time

Essential: • 1-4 years of automotive CAE experience, with a focus on vehicle crashworthiness and occupant-restraint-system development. • 1-2 years of foundational hands-on experience in developing and integrating safety FE models at full-vehicle, subsystem, and component levels, including restraint systems. • Proficiency in PRIMER, ANSA, and LS-DYNA are mandatory. • Strong engineering fundamentals, including a sound understanding of classical and applied mechanics and the operation of basic restraint systems such as single-stage airbags and seatbelts with constant force retractors. • Strong logical reasoning to predict, analyze, and troubleshoot complex nonlinear crash events. . Desirable: • Exposure to Human Body Model (HBM) simulations at sled or vehicle level. • Experience with Linux scripting, Python, Jupyter Notebook, and AI tools. • Good working knowledge of metals, composite components, and failure analysis. • Understanding cross-functional performance requirements. • Experience developing design proposals and collaborating with design engineers to implement them. • Experience working with automotive OEMs in vehicle safety. Key Responsibilities & Tasks • Develop sled buck models from full-vehicle structural models and integrate restraint-system models. • Set up simulation decks with occupants for frontal or side-impact scenarios. • Perform 100ms debug simulations with minimal support. • Load multiple animations, independently complete visual assessments of results, and generate all required plots using the MetaPost OIC toolbar. • Prepare occupant-simulation reports for frontal or side-impact load cases. • Assess and refine model and result quality, ensuring all evaluations are completed on schedule to support project timelines. • Participate in design reviews and recommend improvements to occupant and restraint-system performance. • Collaborate with team members and regularly communicate project updates, findings, and lessons learned during daily virtual or in-person meetings.

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: