BI Team Lead

Overview Overview Parts Authority is one of the largest wholesale automotive parts distributors in the United States, operating 250+ warehouse locations nationwide. We serve thousands of professional automotive repair shops, dealerships, and fleet operators with a comprehensive catalog of OEM and aftermarket parts. Our analytics and data platform is modern and growing: We are investing aggressively in both enterprise BI and AI-driven analytics to become the most data-driven company in our industry. We are seeking a BI Team Lead Sr. who thrives as a coach/player — someone who can lead a team and build production-quality dashboards. This is a hands-on leadership role, not a pure management position. Reporting to the VP of BI (with guidance from the CIO), you will serve as the day-to-day operational leader of our BI delivery team. What You’ll Do Hands-On Report & Dashboard Development & Governance This is where you’ll spend most of your time. You will personally build BI solutions across Power BI, Databricks, and Microsoft Fabric. We need a leader who stays deeply technical. Build production Power BI dashboards, reports, semantic models, and DAX measures that give every part of the business a trusted, governed source of truth for their KPIs. Design and maintain the enterprise semantic layer — shared datasets with standardized dimension models, deployment pipelines, content certification, and row-level security that scales from branch managers to the C-suite. Set the quality bar: conduct code reviews before production deployment, enforce visual design standards, and own the enterprise data dictionary so every metric has a clear definition and owner. Prototype dashboards and reports directly with stakeholders, iterate rapidly, and hand off maintenance to the team once stable. Team Leadership & Delivery Operations You will build a high-performing, structured team from a talented group that needs clear direction and process. Lead a distributed BI team across the US and India. Define roles, set performance objectives, and establish a predictable sprint-based delivery cadence. Own the BI request backlog end-to-end: triage, prioritize by business impact, assign work, and enforce delivery SLAs so stakeholders always know what’s coming and when. Stakeholder Partnership You will be the person stakeholders trust to get them the data they need. Serve as the primary point of contact for BI requests across Sales, Finance, Operations, and Executive leadership — translating ambiguous business questions into precise analytics requirements. Manage expectations proactively: run a formal intake process, communicate timelines clearly, and push back on scope creep constructively. Champion data-driven decision-making by presenting dashboard releases, tracking adoption, and aligning the BI roadmap with evolving business priorities. What Success Looks Like In your first 30 days: You know every person on the team and their strengths, key report and semantic models in production, outstanding analytics request, and stakeholder’s priorities. Team roles are clearly defined and the request intake process is live. In 60 days: New enterprise dashboards and reports are live and actively used. The team has a predictable delivery rhythm and stakeholders see tangible progress. In 3 months: Enterprise dashboards and semantic models are in production across key business functions. Power BI adoption is growing steadily, and the governance framework is operational. In 6 months: Self-service analytics is working — a growing base of monthly users can answer recurring questions without IT involvement. AI capabilities are being integrated into governed dashboards and stakeholder satisfaction is consistently strong. Responsibilities 7+ years of progressive experience in Business Intelligence, data analytics, or data engineering. 3+ years in a team lead or management role directly managing 5 or more people. Hands-on Power BI expert. Deep, current proficiency with Power BI Desktop, Power BI Service, DAX, Power Query/M, semantic models, row-level security, deployment pipelines. Microsoft Fabric experience required. Hands-on experience with Microsoft Fabric, including lakehouses, notebooks, data pipelines, and Direct Lake connectivity. Understanding of how Fabric integrates with Power BI and the broader Azure data ecosystem. Cloud data platform experience. Experience connecting Power BI to cloud data warehouses. Direct experience with Databricks (Delta Lake, Unity Catalog, SQL endpoints) strongly preferred. Azure ecosystem familiarity required. Semantic model development. Proven experience building and managing enterprise semantic models — designing star schemas, defining DAX measures, calculation groups, hierarchies, and relationships that serve as the single source of truth for reporting Distributed team. Experience managing teams across multiple time zones. Comfortable with asynchronous communication patterns and cross-cultural collaboration. Stakeholder management. Ability to partner with business leaders at all levels. You translate ambiguous business questions into precise analytics requirements. Advanced SQL proficiency. Comfortable writing complex queries for ad hoc analysis, data validation, and debugging data quality issues across large, complex schemas. AI-assisted analytics development. Experience using AI tools to accelerate BI workflows — generating DAX measures, writing and optimizing SQL, exploring data models, and drafting documentation. You know how to provide schema context and business rules as input, and you critically evaluate AI-generated output before it reaches production. Coach/player mindset. You thrive in environments where you build and lead simultaneously. You want to stay hands-on with the technology while growing as a leader. Qualifications Industry experience in wholesale distribution, automotive parts, multi-location retail, logistics, or supply chain. Familiarity with legacy ERP environments and mainframe data sources — understanding the data, not programming them. Experience with CDC (Change Data Capture) patterns or similar event streaming technologies. Hands-on experience with AI coding assistants for BI work — using tools like Claude, Copilot, or similar to generate complex DAX, optimize SQL, prototype semantic models, or automate documentation. Bonus if you’ve built prompt templates or workflows that your team reuses. Exposure to AI/ML-powered analytics in production: natural language query interfaces, automated insight generation, or predictive modeling integrated into dashboards. Power BI certifications such as PL-300 (Power BI Data Analyst) or DP-600 (Fabric Analytics Engineer). Experience integrating Power BI with SSO identity platforms. Python scripting for data validation or pipeline collaboration.