Lead Analytics Engineer Enterprise BI & Analytics

About the role
We're hiring a hands-on lead who lives in the data model. You'll be the primary developer behind our Power BI dashboards across the enterprise analytics scope — project profitability, resource utilization and capacity, client finance and pipeline, and FP&A. You'll design star-schema models, write the DAX, build the Power Query pipelines that feed them, and perform the detailed reconciliation and variance analysis that keeps the numbers trustworthy.
This is a unique opportunity to help build the data foundation for a company-wide analytics transformation. Working closely with Finance, Operations, Sales, and HR leadership, your work will directly influence how the business measures performance, makes decisions, and evolves toward a modern, AI-ready data platform. As one of the key technical builders on a growing analytics team, you'll have significant influence over data architecture, modeling standards, and the future direction of our enterprise reporting environment.

What you’ll do

• Own our Power BI dashboards end-to-end across project profitability, utilization/capacity, pipeline/revenue, and FP&A — maintaining and improving the data model, relationships, DAX measures, and report layout.
• Integrate and model data from multiple source systems — CRM (HubSpot), project/time-tracking, finance/ERP, and resourcing (Workday) — into clean, consistent star schemas that hold up across teams, entities, and our regional subsidiaries.
• Build and debug Power Query (M) pipelines with typed column transformations, anti-join patterns for new-record ingestion, normalization, and refresh logic.
• Develop and troubleshoot DAX measures (margin and profitability, utilization rates, coverage ratios, YTD totals, weighted pipeline, budget-vs-actual variance) and diagnose model issues like relationship ambiguity, filter propagation, and grain mismatches.
• Produce the recurring reconciliations and variance analyses leadership relies on — project forecast-vs-actual, utilization vs. plan, and week-over-week pipeline snapshot comparisons.
• Audit source-data quality across systems — flagging date problems, owner gaps, duplicates, and misclassified records before they reach a dashboard — and help strengthen our data governance and data-management standards.
• Build clean, well-documented deliverables (multi-tab workbooks, reusable templates) and make the results clear to business partners and US-based leadership.

Required qualifications

• 5-7 years in data analysis or BI development with significant hands-on Power BI work.
• Strong, demonstrable skills in DAX and Power Query (M) — able to build a model from raw exports to finished dashboard independently.
• Solid data modeling fundamentals (star schema, fact vs. dimension tables, grain), including combining data from several source systems.
• Advanced Excel and comfort with reconciliation/variance work.
• Strong attention to detail and the ability to explain technical results to non-technical stakeholders.
• Strong SQL and working familiarity with cloud data warehouses and ELT tooling.

Nice to have

• Python (pandas) for data matching and reconciliation.
• Experience with project profitability, utilization/capacity, or professional-services finance data.
• CRM (especially HubSpot), project/time-tracking, and finance/ERP data experience (Workday).
• Experience reporting across multiple entities or business units.
• Experience working in an AI-enabled environment, including using AI tools in day-to-day analytics/BI work.