Senior Data Engineer
Summary
Design and maintain Azure Fabric data pipelines (Bronze–Silver–Gold) to transform raw data into analytics-ready datasets for Power BI Embedded reports.
About the Role
We are looking for experienced Data Engineers to design and operate pipelines within the Azure Fabric Medallion architecture (Bronze–Silver–Gold). You\'ll be responsible for transforming raw data into analytics-ready datasets used in Power BI Embedded reports for external and internal users.
Key Responsibilities
Design and maintain data pipelines across Bronze, Silver, and Gold layers using Azure Fabric (Data Factory, Synapse, Lakehouse).
Implement data ingestion from sources like Oracle via Azure Communication Gateway or equivalent connectors.
Develop efficient transformations (SQL, PySpark, or Dataflows) to cleanse and structure data.
Create and optimize Power BI datasets, data models, and DAX measures.
Implement data quality checks and ensure schema consistency across medallion layers.
Collaborate with analysts and developers to embed Power BI dashboards into web applications.
Support occasional data exports to customer data centers or warehouses.
Required Skills
At least 5 years of data engineering experience in designing and implementing enterprise-level data solutions.
Strong understanding of Azure Fabric(Data Pipelines, Lakehouse, Dataflows, Synapse, etc.).
Hands-on experience with Medallion Architecture (Bronze → Silver → Gold).
Advanced SQL and transformation logic (joins, aggregations, incremental loads).
Power BI expertise – dataset modeling, DAX, and performance tuning.
Familiarity with data governance, lineage, and role-based access within Fabric.
Experience building and maintaining production-grade pipelines.
Nice to Have
Exposure to Python or Spark for transformations.
Experience working with Power BI Embedded integration.
Understanding of data warehousing principles and ETL/ELT design.
Familiarity with CI/CD pipelines for data (Azure DevOps, Fabric Git integration).
Leadership/People Management experience.