Data Engineer

Job Information

• Location: Pune
• Job Type: Full-Time
• Work Arrangement: Hybrid
• Relocation Assistance Available: Yes

Key Responsibilities

• Develop and maintain assigned data pipelines using Azure Databricks, PySpark, Spark SQL, SQL, and Delta Lake, building Bronze/Silver/Gold objects to the program s medallion standards.
• Assist with converting legacy Informatica mappings, SQL, and stored procedures into Databricks processing, and support migration of inbound/outbound HR integrations (including Oracle HCM feeds).
• Implement source-to-target mappings and transformation specs, and help build logical/physical, dimensional, and analytics-ready models for HR data domains under senior direction.
• Perform data profiling, unit testing, and defect resolution; build data-quality and reconciliation checks and compare legacy vs. target-state outputs during parallel runs.
• Produce clear technical documentation - mappings, data dictionaries, test cases, runbooks, and deployment instructions - following established naming, repository, and version-control standards.
• Follow MetLife requirements for handling sensitive HR data, applying approved access-control, classification, and governance practices via Unity Catalog and related tooling.
• Participate in agile ceremonies, incorporate code-review feedback, escalate unclear requirements and risks to the Senior Data Engineer, and provide overlap with U.S. Eastern Time.

Required Qualifications

• Bachelor s degree in Computer Science, Information Technology, Data Engineering, or related discipline (or equivalent practical experience), with 2+ years in data engineering, ETL, or data-platform delivery.
• Azure Databricks Spark: 1+ year of practical exposure to Spark, PySpark, Databricks, or a comparable cloud environment, plus working experience with Python and SQL.
• Data fundamentals: Foundational understanding of ETL/ELT, Delta Lake, medallion architecture, data modeling (keys, relationships, normalization, dimensions), and source-to-target mappings.
• AI-assisted engineering: Willingness to use AI/Copilot tooling to accelerate development, testing, and documentation.
• Curious, detail-oriented, and coachable - able to follow technical direction, apply code-review feedback, and produce accurate, well-tested, well-documented work.
• Strong written and verbal communication, comfortable raising questions and blockers clearly within a distributed agile delivery team.

Preferred Qualifications

• Suggested 1-2 years exposure to data migration or ETL modernization (e.g., Informatica-to-Databricks) and building pipelines within a team environment.
• Azure ecosystem: Data Lake Storage, Data Factory, DevOps, Azure SQL/Synapse, Unity Catalog (or Microsoft Purview), and Git-based CI/CD practices.
• HR domain data: Oracle HCM Cloud extracts/PVOs/HDL, or workforce, employee, organization, position, talent, and related HR data.
• Microsoft Azure or Databricks coursework/certification, and experience supporting U.S.-based enterprise clients from an offshore delivery model.
• Experience in insurance, financial services, HR technology, or another regulated, highly governed data environment.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.