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Tier-1 brand, mid-level generalist data role, metro/offshore and broad required skills increase competition.
Core data engineering skills transferable, but Databricks/AWS platform experience favors data-focused backgrounds.
Explicit 5+ years plus mandatory Databricks and AWS data platform experience enforce strict filters.
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Lead and support migration, operation, and optimization of data pipelines in a Databricks-on-AWS lakehouse environment.
Manage and guide a small offshore engineering team to ensure reliable, secure, and scalable data workflows using AWS services and Databricks features.
Collaborate with platform and governance teams to align engineering delivery with enterprise standards, including CI/CD, monitoring, and operational readiness.
Minimum 5+ years of experience in data engineering or related pipeline development roles.
Hands-on experience with Databricks and AWS data engineering stack including Amazon S3, AWS Glue, AWS IAM; familiarity with AWS Lake Formation, Amazon Athena, AWS Lambda preferred.
Proficiency in Spark, SQL, and Python with knowledge of Delta Lake, Unity Catalog, and open table/storage formats such as Apache Iceberg.
Work Experience Required: 5+ years in data engineering roles; Notice Period: Not explicitly mentioned in the JD.
Experienced in managing data pipeline onboarding, migration, and operational support within enterprise-scale Databricks-on-AWS lakehouse platforms.
Skilled in operational excellence using CI/CD, infrastructure as code, monitoring tools, and cloud-native orchestration within regulated, secure environments.
Strong in cross-team collaboration with offshore teams and governance/cloud platform stakeholders to deliver governed, scalable, and compliant data engineering solutions.