Analytics Engineer

Key Responsibilities

• Data modeling & SQL: Design, build, and maintain SQL views, staging tables, and fact/dimension models in our Azure SQL data warehouse, including deduplication and business-rule logic (e.g., status-based routing, multi-source reconciliation).
• Semantic models & reporting: Build and maintain Power BI semantic models — relationships, DAX measures, security roles — and the reports and dashboards built on top of them for business stakeholders and company-wide reporting.
• Pipeline support: Share responsibility with the Sr. Manager, Data & Analytics for monitoring scheduled Azure Data Factory pipelines and Power BI dataset refreshes. Respond to failures and perform basic troubleshooting.
• Pipeline modifications: Make minor modifications to existing pipelines to support new or changing business requirements, as your familiarity with the tooling grows.
• Business partnership: Partner with business SMEs to translate reporting requests and business logic (commission structures, revenue recognition, inventory rules, etc.) into accurate, well-documented data models.
• Documentation: Write and maintain documentation for data models, metric definitions, and report logic so that data lineage and ownership are clear beyond any one person.
• Standards & quality: Follow and help evolve team standards for naming conventions, DAX style, and semantic model design as the team's practices mature.
• Continuous Improvement: Proactively identify opportunities for process improvements, optimize current data workflows, and incorporate new technologies or tools to enhance data analytics capabilities.

Required