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Metro Hyderabad, popular data-engineer title, broad AWS/ETL requirements increase candidate competition to medium.
Medium because core cloud data engineering skills transfer easily but finance/regulatory experience is preferred.
High due to explicit 8+ years requirement and mandatory AWS, ETL, orchestration, IaC and leadership experience.
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Lead a high-performing team to design, build, and modernize cloud-native data ingestion, integration, and API services in AWS.
Architect and execute migration of legacy data pipelines to scalable, governed, cloud data ecosystems using AWS services like S3, Glue, Lambda, Kinesis.
Define engineering standards and best practices to support federated data product models, ensuring automation, observability, and data governance compliance.
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 degree preferred.
Hands-on experience with AWS cloud data lake architectures (S3, Glue, Lake Formation, Snowflake), data governance tools (e.g., Unity Catalog, Collibra), and pipeline orchestration tools (Airflow, Step Functions).
Proficiency in Python and/or SQL, plus experience with DevOps practices including Terraform or CloudFormation, CI/CD, and monitoring.
Demonstrated leadership in building and managing engaged, high-performance engineering teams focused on data modernization and cloud migration.
Expertise in designing and operating scalable, secure, automated data pipelines and APIs within AWS cloud environments.
Experience collaborating cross-functionally with architecture, analytics, AI, and governance teams in regulated or financial services contexts.