Senior Data Engineer I

3 days ago

Bengaluru, IndiaEntry Level

Responsibilities

Lead end-to-end development of robust data pipelines, models, and integration flows across AWS, Azure, Databricks, and GitHub.
Architect, optimise, and automate Databricks workflows, including Jobs, Delta Live Tables, Unity Catalog, cluster policies, and cost governance.
Build analytics- and AI-ready datasets for forecasting, optimisation, automation, and self-service insights.
Implement data quality, lineage, observability, governance, security, and relevant GxP compliance controls.
Drive platform stability, reduce incidents, and champion continuous improvement.
Mentor junior engineers and contribute to standards, patterns, and reusable components.
Collaborate with manufacturing and supply chain business teams, AI Foundation, enterprise platform teams, and other IT colleagues on scalable data platforms.

At least 8 years of experience in data engineering.
Strong SQL, Python, and Spark-based development skills.
Hands-on Databricks experience with notebooks, orchestration, workflows, Delta Lake, and Unity Catalog.
Experience with the Azure data stack, including Azure Data Factory, Azure Databricks, and GitHub.
Experience managing and deploying infrastructure as code and CI/CD processes.
Experience building and enforcing data quality frameworks, rules, and code-quality checks.
Strong problem-solving and communication skills.
Supply chain systems experience in planning, logistics, or warehousing is useful but not essential.
Exposure to ML workflows, MLOps, or Databricks ML is useful but not essential.
Cloud or Databricks certifications are useful but not essential.

Opportunities to build new skills, mentor others, and grow through hands-on experience and relevant learning offerings.
Supportive environment with feedback and opportunities to contribute to platform decisions.
Inclusive recruitment process and equal opportunity for applicants.
Application deadline: 26th Nov 2026.