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Tier-1 brand, metro role, broad generalist data skillset, and high visibility increase candidate competition.
Strong platform-specific (Synapse/Databricks) and enterprise governance requirements limit cross-industry transferability.
Mandatory 10+ years and specific Azure/Databricks platform requirements enforce strict shortlisting.
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Lead technical assessment, re-engineering, and migration strategy for existing enterprise data platform from Azure Synapse to Azure Databricks Lakehouse.
Own end-to-end validation and documentation of complex data pipelines, data models, transformation frameworks, and governance controls ensuring correctness and defect remediation.
Design and implement target architectures adhering to modern lakehouse principles and manage parallel-run validations before production cutover.
10+ years of experience in Data Engineering with significant platform migration or re-engineering experience.
Mandatory hands-on expertise in Azure Synapse Analytics (Pipelines, Spark Pool, Dedicated SQL Pool), ADLS Gen2, Delta Lake, Azure Databricks (PySpark, Spark SQL), and data governance frameworks.
Strong programming skills in Python and SQL with experience in large scale ETL/ELT processes and complex data source integrations (Oracle, SQL Server, Salesforce, APIs).
Work Experience Required: 10+ years; Notice period: Not explicitly mentioned in the JD.
Experienced in auditing and owning complex enterprise data platforms with ability to reverse-engineer and validate existing implementations rather than greenfield development.
Comfortable balancing hands-on engineering with technical architecture responsibilities across multi-stakeholder enterprise environments, ideally regulated sectors (financial services a plus).
Skilled in executing migration strategies preserving governance, data quality, audit, reconciliation, and governance frameworks during transitions.