Data Pipelines & Integration

• Design, build, and maintain scalable batch/streaming pipelines (e.g., telematics/IoT, SAP, PLM, MES, service/warranty, dealer systems).
• Implement CDC, schema evolution, and data quality checks (Great Expectations/Deequ/custom).
• Develop feature pipelines for ML and analytics (feature stores, time-series transformations).

Data Modelling & Storage

• Model data for lakes/lakehouses/warehouses (Delta/Parquet/Iceberg) following medallion or similar architectures.
• Optimize partitioning, compaction, and performance for large datasets.

AI/ML Enablement

• Partner with Data Scientists to productionize models (batch/real-time), build inference pipelines/APIs, and manage feature stores.
• Contribute to MLOps (CI/CD for models and data, model versioning, monitoring, drift detection).
• Support GenAI use cases (RAG pipelines, vector indexing, prompt orchestration, governance).

Platform & DevOps

• Implement infrastructure‑as‑code, CI/CD and observability (lineage, cataloging, logging/metrics).
• Enforce security, privacy, and compliance (PII handling, role-based access, data contracts).

What you will have

• Bachelor’s or master’s degree in computer science, Data Engineering, Industrial Engineering, or related field.
• Overall, at least 7+ years of experience in Data engineering
• Strong proficiency in Snowflake, SQL, Python, and ETL tools (e.g. Snaplogic).
• Familiarity with cloud platforms (AWS, Azure, GCP) and data warehousing solutions (e.g., Snowflake, Redshift).

AI/MLOps Exposure:

• Building feature pipelines, packaging and deploying models (batch/real‑time).
• Model serving (Databricks Model Serving, MLflow, Azure ML etc), model registry, experiment tracking.
• Familiarity with vector databases and RAG patterns.

Behavioural Competencies

• Ownership & bias for action; thrives in a product operating model.
• Clear communicator who can bridge business and engineering.
• Pragmatic, security‑first, automation‑oriented mindset.
• Collaborative partner across global, cross‑functional teams.
• This position requires candidate to work a 5-day -a -week schedule in the office
  • Shift Timing-01:00PM-10:00PM IST