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Mid-level generalist data engineering role with common skills and hybrid hiring increases competition.
Core data engineering skills transfer broadly, though revenue-system and Fabric requirements narrow applicability.
Requires 5+ years and specific Microsoft Fabric/Azure/dbt expertise, tightening candidate filters.
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Own and build the Revenue Data Platform integrating core revenue systems into trusted analytics-ready datasets within a modern lakehouse architecture using Microsoft Fabric technologies.
Design, implement, and maintain dimensional data models and ELT pipelines supporting reporting, forecasting, and revenue analysis across multiple business units.
Ensure data quality, observability, governance, and support historical revenue analysis while collaborating with cross-functional teams for scalable data solutions.
5+ years of experience in data engineering, analytics engineering, or data platform roles building production data systems.
Proficiency with Microsoft Fabric or comparable modern data platforms (e.g., Databricks, Azure Data Factory) and experience with Azure cloud services including ADLS Gen2, Azure DevOps, and access management.
Strong expertise in dimensional data modeling, slowly changing dimensions, snapshots, SQL transformations, and data quality/observability practices.
Work Experience Required: 5+ years
Experienced in building and optimizing production ELT pipelines within Microsoft Fabric or similar lakehouse environments in Azure cloud.
Skilled in translating business revenue operations and marketing requirements into scalable data models and analytics solutions.
Capable of driving data platform engineering best practices including testing, CI/CD, documentation, and mentoring junior engineers or analysts.