Our client, a US furniture retailer, is currently expanding their Data team and is looking for strong talents.
Responsibility:
1. Data Ingestion & Preparation:
- Build and manage data pipelines (using Dataflow Gen2 / Fabric pipelines) to standardize silver => gold layers.
2. Data Modeling:
- Design and implement star schema / dimensional models
- Build Golden Tables that are clean, standardized, and optimized for analytics/BI consumption.
3. Data Transformation
- Use Dataflows to clean, transform, and enrich silver data to business-ready golden tables.
- Implement incremental load strategies to optimize refresh times and performance.
4. Data Quality & Governance
- Implement validations, deduplication, and business rules in dataflows.
- Appy data lineage tracking and document transformations from source => golden.
5. Optimization & Performance
- Tune queries for Lakehouse / Warehouse performance.
- Implement partitioning, incremental refresh, and indexing strategies for large fact tables.
6. Collaboration
- Work with business analysis to understand reporting needs.
- Parter with data scientists to ensure golden tables support advanced analytics and ML.
Technical skills:
- Strong SQL (T-SQL / DAX / M query for Power Query).
- 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
Qualification:
- Level: Mid-Senior Staff (not entry, needs strong technical grounding)
- Experience: 3-5 years in data engineering or BI development
- Hands-on with SQL Server, Azure Data Factory / MS Fabric pipelines, Dataflows, Power BI 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, FMGC, or retail data projects (bonus)
