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Job Description
Key Responsibilities
Data Pipeline & Product Development
• Design, develop, and maintain scalable data pipelines on AWS using Databricks, PySpark, Python, and SQL
• Build and maintain data products following the Medallion architecture — Bronze (raw ingestion), Silver (cleansed/conformed), Gold (business-ready)
• Develop data transformations and processing workflows using PySpark, Spark SQL, and Python
• Build analytics-ready datasets and reusable data assets following the POC → Pilot → Prod governance pathway
• Apply data modeling concepts including dimensional modeling, Star Schema, and domain-oriented data product design
Platform & Infrastructure
• Build and support solutions on AWS data services — S3, Glue, Step Functions, Lambda, Athena, and CloudWatch
• Work with Apache Iceberg table format for open, high-performance Lakehouse storage
• Develop and optimize Snowflake objects (tables, views, stored procedures) as the SQL consumption layer
• Support orchestration workflows using AWS Step Functions or Apache Airflow
• Implement CI/CD and deployment processes using Git, GitHub Actions, and infrastructure-as-code practices
Data Quality & Governance
• Implement data quality, validation, reconciliation, and monitoring processes — including SOX-compliant controls for close-critical financial data
• Support data contracts and observability — ensuring data products meet defined schema, freshness, and quality thresholds
• Implement data security practices including RBAC, data masking, and access controls
• Monitor data pipeline health, data quality, and cloud platform performance
• Participate in Databricks Unity Catalog governance and metadata management
Stakeholder Collaboration
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📌 Data Engineer (Bengaluru)
🏢 3M
📍 Bengaluru