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Tier-1 brand, popular data-engineer role, metro hiring and broad cloud/Databricks requirements raise competition.
Data platform skills are transferable but enterprise governance and domain nuances require moderate background alignment.
Explicit 8+ years plus mandatory Databricks/AWS/Spark/Python stack enforces strict candidate filtering.
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Lead and support data pipeline onboarding, migration, and operational activities within a Databricks-on-AWS lakehouse environment.
Manage and mentor a small offshore engineering team while ensuring high-quality execution of scalable, secure, and governed data workflows using AWS services and Databricks capabilities.
Maintain operational excellence through deployment, monitoring, incident management, and cloud-native automation including CI/CD and infrastructure as code.
8+ years of experience in data engineering or related pipeline development roles.
Hands-on experience with Databricks, Spark, SQL, Python, and AWS data engineering services such as Amazon S3, AWS Glue, and AWS IAM.
Familiarity with Databricks Unity Catalog, Delta Lake, and data governance concepts; knowledge of AWS Lake Formation and Athena preferred.
Work Experience Required: 8+ years (explicitly mentioned). Notice period: Not explicitly mentioned.
Experienced in enterprise-scale data platform migration, onboarding, and pipeline operational support in a cloud (AWS) environment.
Proficient in applying engineering best practices in CI/CD, source control, automated testing, and monitoring for complex data workflows.
Skilled at guiding and collaborating with offshore teams, ensuring alignment with enterprise AWS standards and secure governance frameworks.