Senior Data Engineer
- Рівень:
- senior
- Джерело:
- djinni.co
Що робити
- Data Pipeline & Framework Development: Design, build, and orchestrate robust end-to-end data pipelines using Dataflows Gen2, PySpark notebooks and native orchestration tools.
- Architecture & Storage Layer Management: Implement and maintain Medallion Architecture (Bronze, Silver, Gold layers), ensuring proper incremental loading strategies and layer-specific transformation logic.
- Data Warehousing & Dimensional Modelling: Build Kimball-style fact and dimension models, manage Slowly Changing Dimensions (SCDs), and ensure Gold-layer data conformance for analytics consumption.
- Data Transformation & Optimization: Write clean, modular Python/PySpark code and T-SQL/DDL logic for data cleansing, schema design, stored procedures, and query performance tuning.
Що очікуємо
- Must-Have Skills:
- Python / PySpark for Data Engineering: Strong experience writing PySpark notebooks in Fabric, building data transformation/cleansing logic, and notebook-based pipeline development.
- Medallion Architecture: Proven expertise in designing and implementing Bronze/Silver/Gold layered ingestion-to-consumption patterns, incremental loading, and transformation logic.
- Dimensional Modelling: Strong knowledge of Kimball-style fact/dimension design, SCD (Slowly Changing Dimension) handling, and Gold-layer conformance.
- T-SQL & DDL Proficiency: Expertise in warehouse schema design, writing stored procedures, and performance tuning.
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