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Tier-1 brand, mid-senior generalist data role with broad skillset and metro appeal.
Medium: core data engineering skills transfer broadly, but HR domain and enterprise modernization increase domain specificity.
High: explicit 5+ years requirement plus mandatory technical stack, leadership, cloud, and governance experience.
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Lead enterprise-scale modernization of legacy HR data warehouses and ETL platforms to cloud-native, AI-enabled Lakehouse architectures using Medallion design principles.
Design, develop, and optimize scalable, secure data platforms and pipelines leveraging Python, PySpark, SQL, and ETL/ELT frameworks on cloud platforms like Microsoft Fabric.
Drive migration strategies and execution for large-scale legacy data environment transformations ensuring data integrity and business continuity.
5+ years of Database Engineering or equivalent experience.
Experience leading enterprise-scale data modernization initiatives (5-10+ years in data engineering recommended).
Proficiency with Python, Apache Spark/PySpark, SQL, ETL/ELT design, and API integration.
Not explicitly mentioned: Notice period and mandatory educational degree.
Experienced in Cloud Data Platforms with demonstrated skills in Lakehouse, Data Mesh, and Data Fabric architectures.
Proven track record in migrating large-scale on-premise data environments to cloud platforms (Azure, Microsoft Fabric, GCP, or Databricks).
Capable of leading complex, multi-stakeholder technical initiatives with strategic impact in HR/Enterprise data domains and familiarity with AI/ML integration in data engineering.