Data Engineer
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Location
In office (Pune)
Experience
7+ years exp
Visa
Sponsors visas in United States; no register of this country names it
Employment
Full-Time
First seen by Alion on Nov 7, 2026.
Overview
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Impact
Profile match
MetLife is an insurance and financial services company that offers life insurance, annuities and employee benefits, and manages investments. It hires engineers, data and analytics leads and finance and infrastructure managers, with a large technology team in Kuala Lumpur. The company is headquartered in New York, United States.
Backed by Stone Point Capital
Key Responsibilities
- Design, develop, test, and deploy scalable pipelines using Databricks, PySpark, Spark SQL, and Delta Lake, spanning Bronze/Silver/Gold (medallion) layers for HR data integration and analytics.
- Build data models – logical, physical, dimensional, and integration – and maintain source-to-target mappings for workforce, organization, employee, position, job, and related HR domains.
- Migrate legacy GDC integrations by re-engineering Informatica, SQL, and stored-procedure logic into modern Databricks patterns, including inbound Oracle HCM feeds and outbound HR data files.
- Validate output parity through reconciliation, parallel runs, and source-to-target checks, and build automated data quality, exception handling, and audit controls into pipelines.
- Apply enterprise governance, security, privacy, and role-based access expectations to sensitive HR data, capturing lineage and metadata where applicable.
- Produce production-ready documentation – technical designs, runbooks, data dictionaries, and support handoffs – for maintainable, observable, cost-aware solutions.
- Collaborate within a distributed delivery team, participate in agile ceremonies, mentor junior engineers, and communicate progress, blockers, and risks clearly.
- Bachelor's degree in Computer Science, Engineering, or related field, with 7+ years of data engineering, ETL, or data platform experience.
- Azure Databricks & Apache Spark: 3+ years hands-on building Delta Lake pipelines with PySpark, Spark SQL, and SQL across a medallion architecture.
- Data modeling & integration: Strong logical/physical/dimensional modeling plus source-to-target mapping, reconciliation, and production cutover support.
- AI-assisted engineering: Proficiency using AI/Copilot tooling to accelerate development, code conversion, and documentation.
- Practical, delivery-focused work style, comfortable turning ambiguous legacy logic into clean target-state designs within a highly governed environment.
- Strong written and verbal communication, with the ability to overlap U.S. Eastern Time for key meetings, design reviews, and issue resolution.
- Suggested 3+ years modernizing legacy ETL (Informatica-to-Databricks) or building metadata-driven, configuration-driven data frameworks.
- Azure ecosystem: Data Lake Storage, Data Factory, DevOps, Azure SQL/Synapse, Unity Catalog, and Git-based CI/CD.
- HR domain data: Oracle HCM Cloud extracts/PVOs/HDL, workforce analytics, and consumption via Power BI, Crunchr, or similar.
- Experience supporting regulated, sensitive employee data in insurance, financial services, or HR technology.
- Detail-oriented, collaborative, and comfortable working independently against offshore delivery expectations while staying aligned to MetLife leads.
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