Data Analytics Engineer

Role & responsibilities

• Design and implement our data lakehouse on Microsoft Fabric including OneLake, Lakehouses, Warehouses, Data Pipelines, and Dataflows Gen2.
• Build and maintain ELT/ETL pipelines to ingest and transform data from Oracle NetSuite, Salesforce, Rippling, Arena PLM, and other enterprise systems.
• Develop and maintain semantic models (Power BI datasets / Direct Lake) and dimensional data models (star/snowflake schemas)
• Create executive and operational dashboards and reports using Power BI (within the Fabric workspace).
• Apply data modeling best practices: dimensional modeling, slowly changing dimensions, data vault patterns where appropriate.
• Collaborate with business stakeholders to define KPIs, metrics, and reporting requirements translating them into scalable data products.
• Implement data governance practices: data cataloging, lineage, quality monitoring, and access controls within Microsoft Fabric.
• Optimize query performance across Fabric Lakehouse (Spark) and Warehouse (SQL endpoint) layers.
• Partner with the Integrations team to ensure clean, reliable data from source systems through the integration layer.

Establish and maintain documentation for data models, pipelines, and data dictionaries.

Preferred Candidate:

• 5+ years of experience in data engineering, analytics engineering, or BI development.
• Hands-on experience with Microsoft Fabric OR strong experience with Azure Synapse Analytics / Azure Data Factory / Power BI (and willingness to upskill to Fabric).
• Strong SQL skills query optimization, window functions, CTEs, and analytical queries.
• Experience building ELT/ETL pipelines from enterprise SaaS applications (ERP, CRM, HRIS).
• Familiarity with Python or PySpark for data transformation workloads
• Understanding of data governance, data quality, and metadata management concepts
• Strong analytical thinking and ability to translate business questions into data solutions.
• Experience with dimensional data modeling (star schema, facts, dimensions) and BI best practices.
• Proficiency with Power BI report development, DAX, data model optimization.