Role & responsibilities
Data Engineering & Lakehouse: Monitor, orchestrate, and troubleshoot scheduled ETL/ELT pipelines using Microsoft Fabric, Lakehouse, OneLake, and Delta tables. Write SQL, notebooks, or PySpark scripts to fix transformation or data quality issues across Bronze/Silver/Gold layers.
Power BI & Analytics: Provide L2/L3 support for Power BI semantic models, reports, and dashboards. Troubleshoot refresh failures, optimize DAX measures and Power Query transformations, and deliver minor report enhancements.
Incident & Production Support: Conduct root-cause analysis for failed data loads, reconciliation discrepancies, or dashboard anomalies. Support production releases, deployments, and integration connectivity (APIs, ERP/SAP sources)





Preferred candidate profile
3+ years of experience across Data Engineering or Business Intelligence/Power BI settings.
Robust SQL proficiency and deep understanding of data warehousing, dimensional modelling, and star schemas.
Hands-on experience with Power BI Desktop/Service and DAX, alongside core ETL/ELT pipeline concepts.
Exposure to cloud data platforms (Microsoft Fabric, Azure Data Lake, Delta Lake, or PySpark).
Prior experience in production support (L2/L3), incident management, and data reconciliation.

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