Senior Data Engineer

Responsibilities:

• Data Ingestion & Preparation: Build and manage data pipelines (using Dataflow Gen2 /Fabric pipelines) to standardize silver -› gold layers.
• Data Modeling:
  • Design and implement star schema / dimensional models.
  • Build Golden Tables that are clean, standardized, and optimized for analytics/BI consumption.
• Data Transformation:
  • Use Dataflows to clean, transform, and enrich silver data into business-ready golden tables.
  • Implement incremental load strategies to optimize refresh times and performance.
• Data Quality & Governance:
  • Implement validations, deduplication, and business rules in dataflows.
  • Apply data lineage tracking and document transformations from source -› golden.
• Optimization & Performance:
  • Tune queries for Lakehouse / Warehouse performance.
  • Implement partitioning, incremental refresh, and indexing strategies for large fact tables.
• Collaboration:
  • Work with business analysts to understand reporting needs.
  • Partner with data scientists to ensure golden tables support advanced analytics and ML.

Skill:

• Technical Skills:
  • Strong SQL (T-SQL / DAX / M query for PowerQuery).
  • Experience with Microsoft Fabric components: One Lake, Dataflow Gen2, Lakehouse, Warehouse, Semantic Models.
  • Data modeling expertise (star schema, fact/dim design, slowly changing dimensions).
  • ETL/ELT concepts and incremental refresh strategies.
• Analytical Skills:
  • Ability to translate business metrics (e.g., forecast accuracy, sales performance, supply chain KPIs) into reusable golden tables.
  • Strong grasp of data lineage, data quality, and governance.
• Cloud & Modern Data Stack:
  • Experience with Azure Synapse / Data Factory is a plus (migration mindset from dedicated pools to One Lake).
  • Familiarity with Power BI integration and how semantic models feed dashboards.
• Soft Skills:
  • Strong communication to bridge business needs and technical implementation.
  • Documentation of golden table definitions and refresh logic.

Experience Required:

• 3-5 years in data engineering or Bl development.
• Hands-on with SQL Server, Azure Data Factory / MS Fabric pipelines, Dataflows, PowerBl datasets.
• Strong in ETL / ELT, data modeling (star schema), performance tuning.
• Some exposure to cloud migration projects (on-prem SQL -> Fabric/OneLake is a big plus).
• Has worked in supply chain, FMCG, or retail data projects (bonus).