Sr Engineer, Data Analytics Engineering
LPL Financial (company site, opens in a new tab)8+ yrsHyderabadOn-siteDirect career pageEst. 28–45 LPA
Posted on 3 Sept
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Job description
Structured overview of role & requirements
About This Role
- Lead and develop a high performing team responsible for designing, building, and modernizing cloud-native data ingestion, integration, and API services within AWS.
- Architect and implement scalable batch, streaming, and event-driven data pipelines using AWS services like S3, Glue, Lambda, and Kinesis, while embedding governance (metadata, lineage, security, quality).
- Drive modernization by migrating legacy SQL/SSIS/ETL pipelines to cloud-native patterns and define engineering standards across federated data product teams.
Minimum Requirements
- 8+ years of experience in data engineering, software engineering, and/or cloud engineering.
- Bachelor’s degree in Data Science, Computer Science or related field (Master’s preferred).
- Hands-on experience with AWS data lake architectures (S3, Glue, Lake Formation, Snowflake or similar), pipeline orchestration (Airflow, Step Functions, dbt), and devops tools (Terraform/CloudFormation, CI/CD).
- Proven track record of leading and developing high performing teams.
Ideal Candidate Profile
- Experienced leader combining deep hands-on cloud data engineering skills and strong architectural instincts to guide modernization at scale.
- Familiar with data governance, cataloging tools (Unity Catalog, Collibra, Atlan, AWS Glue Data Catalog), and security/compliance requirements, preferably in regulated domains like financial services.
- Demonstrates ability to collaborate cross-functionally with architecture, analytics, AI, governance, and security teams to deliver scalable, governed cloud data platforms and APIs.