Solid understanding of data lakehouse patterns and Delta Lake / OneLake concepts, with the ability to structure data models that are AI/ML-ready and support semantic modeling.
Solid understanding of SQL, relational and dimensional data modeling, query tuning, and basic performance optimization.
Familiarity with data quality concepts — null/duplicate/schema-drift checks, basic SCD handling, and validation rules in transformation pipelines.
Familiarity with Git, branching strategies, and CI/CD concepts in a data engineering context (Azure DevOps or GitHub Actions).
Strong communication and collaboration skills, with the ability to articulate complex data engineering solutions to both technical and non-technical stakeholders, and to lead cross-functional initiatives.
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