Data Engineer

YOUR WORK ENVIRONMENT

At MAN India, we offer a state-of-the-art and modern work space. Our engineers work on the latest and advanced technologies in the automotive world with the latest hardware and software. We offer a conducive ecosystem for our engineers to learn and perform. Furthermore, the office space includes a spacious cafeteria, breakout areas, recreational facilities as well as space for conferences and meetings.

JOB PURPOSE/ROLE

As a member of our team you will have the following tasks:

Lead end-to-end data engineering and architecture to build scalable, reliable, and high-quality data solutions for business, analytics, and AI. Drive data strategy, AI/ML enablement, performance, governance, and team collaboration while ensuring secure and production-ready solutions

• Lead processing and decoding of large-scale, multi-terabyte datasets.
• Shape platform architecture and deliver trusted data foundations for business, analytics and AI.
• Experienced towards self-developing as AI-Forward Deployed Engineer (AI-FDE).
• Assemble large, complex datasets that meet business and analytics requirements.
• Architect and implement ETL/ELT infrastructure using Python, PySpark, SQL and AWS big-data services.
• Build analytics tooling on top of pipelines to deliver actionable business insights.
• Lead performance, reliability, security, observability and cost optimization.
• Define engineering standards for CI/CD, testing, data contracts, lineage and operations.
• Guide design reviews, mentor engineers and align solutions with business stakeholders.

AI & Data Science Enablement

• Define data architecture for GenAI, machine learning and advanced analytics workloads.
• Establish governed feature, training, inference and feedback data patterns across the AI lifecycle.
• Partner with data science and AI leaders on scalability, reproducibility, responsible AI data controls and production readiness.

Delivery & Collaboration

• Translate business and analytics needs into reliable, reusable data products.
• Apply Git-based development, CI/CD, testing, documentation and operational monitoring.
• Partner with analysts, data scientists, platform teams and business stakeholders.

Success Indicators

• Trusted datasets delivered with measurable quality, lineage and service reliability.
• Faster analytics and AI use-case delivery through reusable, governed data assets.
• Secure, cost-aware and maintainable solutions aligned with platform standards.

YOUR QUALIFICATIONS

Must Have

• Experience:  5 to 8 years
• Qualification B.E./B.Tech/ M. Tech with relevant experience
• Strong production-grade Python and real production experience with Spark/PySpark distributed processing.
• Advanced SQL, query optimization and data modeling expertise.
• Hands-on AWS expertise across S3, Glue, Athena, Lambda and IAM.
• Proven ownership of production ETL/ELT pipelines at scale.
• Architecture knowledge across Data Lake, Data Warehouse and RDS patterns.
• Experience with Apache Iceberg, Hive and AWS Lake Formation.
• Strong GitLab CI and modern software engineering discipline.

Software Skills

• Python, PySpark, SQL. AWS: S3, Glue, Athena, Lambda, IAM. Big Data & Analytics: ETL/ELT, Data Pipelines, Data Architecture. AI/ML: GenAI, Machine Learning, MLOps. CI/CD: Git, GitLab CI..

Good to have

• Automotive domain exposure, especially vehicle, fleet or telemetry data. Infrastructure as Code using AWS CDK, Terraform, CloudFormation or equivalent. Event-driven services such as SQS, SNS, EventBridge and Step Functions.