Data Engineer - Enterprise Data Lakehouse & Data Products
3M (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 14–24 LPA
Posted 5h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead design and delivery of scalable data pipelines and data products on 3M's AWS-based Enterprise Data Lakehouse using Databricks, PySpark, Python, and SQL within a Medallion architecture.
- Implement data quality, validation, reconciliation, monitoring controls including SOX-compliant controls for financial data, RBAC, and data masking.
- Partner with cross-functional teams (Finance, Supply Chain, R&D, Tax, Commercial) to identify data needs and deliver reusable analytics-ready datasets through POC to Production lifecycle.
Minimum Requirements
- Bachelor's degree or higher in Computer Science, Information Technology, Engineering, or related discipline.
- 5+ years of experience in data engineering or analytics engineering (private, public, government, or military environment).
- Hands-on experience with SQL, relational databases, Python, PySpark, Databricks, AWS data services (S3, Glue, Lambda, Athena), and Lakehouse/Medallion architecture.
- Experience developing and supporting production data pipelines using Git and CI/CD, with knowledge of data modeling, data quality, validation, and monitoring.
Ideal Candidate Profile
- Experienced in operating AWS-based data platforms with strong skills in Databricks and Lakehouse architecture.
- Demonstrates ability to implement data governance including SOX compliance and RBAC in enterprise-scale financial data environments.
- Collaborates effectively with cross-disciplinary business and technical teams to translate requirements into reusable, scalable data products.