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Senior data engineering role in Hyderabad with specific cloud and governance skills yields medium competition.
Core data engineering skills transfer across industries, though finance regulatory experience is favored.
Explicit 8+ years and many mandatory AWS, governance, and leadership skills increase strictness.
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.
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.
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.