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Niche data platform skills and senior title reduce applicant pool despite lesser-known employer and unspecified location.
Core data engineering skills transfer across industries, but SAP and lakehouse experience increases domain specificity.
Requires specific lakehouse, ETL/orchestration, governance, and leadership skills, so filters are moderately strict.
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Develop and maintain enterprise-scale data pipelines across ingestion, transformation, storage, and serving layers.
Implement and optimize lakehouse architectures using platforms like Databricks, Microsoft Fabric, or Snowflake and enforce data governance and compliance frameworks.
Lead and mentor data engineers, drive DataOps practices including CI/CD and Infrastructure as Code, and transition PoCs to production-grade deployments.
Experience with building and maintaining data pipelines using ETL/ELT tools such as Azure Data Factory or equivalent.
Hands-on experience in data platforms involving medallion architecture (Bronze/Silver/Gold) on Databricks, Microsoft Fabric, or Snowflake.
Proficiency in PySpark and SQL coding standards, including performance tuning and cloud cost optimization.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced leader with a strong technical background in modern data platform architectures and enterprise analytics.
Skilled in data governance, security, and compliance implementation within data engineering workflows.
Capable of managing end-to-end data solution delivery including DevOps best practices and mentoring junior team members.