BI Engineer

Loenbro•Centennial, CO

1d•$100,000 - $125,000•Hybrid

About The Position

The Business Intelligence Engineer is the external-facing half of Loenbro’s data team. This person works alongside the Senior Manager of Business Analytics to gather requirements from the business. They work with operations leaders, project finance teams, field stakeholders, and department heads to understand what decisions they need to make — and then build the reports and dashboards that give them that visibility. The BI Engineer consumes the trusted data models produced by the Analytics Engineering team and transforms them into clear, validated, business-ready reporting. This role requires as much people skill as technical skill: you are the bridge between the data platform and the people who use it every day.

Requirements

Bachelor’s degree in Business Analytics, Information Systems, Finance, Computer Science, or related field
3–5 years of experience in business intelligence, data analytics, or a reporting-focused role
Demonstrated experience working directly with business stakeholders to define KPIs, metrics, and reporting requirements
Construction, field operations, or project finance background preferred — understanding of job costing, budget vs. actual tracking, and operational workflows is a meaningful advantage in this role
Power BI — required; designing, publishing, and maintaining interactive dashboards, operational reports, and executive-level visualizations
DAX — required; calculated columns, measures, time intelligence, and KPI logic
Power Query (M) — shaping and transforming data within the Power BI and Fabric environment
Microsoft Fabric — working knowledge of how data flows from source through the medallion layers to the reporting layer; comfortable consuming gold-layer datasets
Semantic model consumption — ability to build reliable reports on top of models produced by the Analytics Engineering team
Row-level security (RLS), workspace governance, and report deployment best practices
Data validation techniques — cross-checking report outputs against source data and business-defined logic
Solid understanding of medallion architecture — knows how data is structured across bronze/silver/gold and which layer to consume for which use case
Familiarity with ETL/ELT concepts — enough to have informed conversations with the Analytics Engineering team about data availability and pipeline timing
Fact and dimension table literacy — understands how a well-modeled dataset enables better, more flexible reporting
Basic to intermediate SQL for querying, validating data, and troubleshooting report discrepancies

Nice To Haves

Power Platform experience (Power Apps, Power Automate) for lightweight workflow and form-based solutions
Project finance or job costing knowledge — how construction companies track costs, contracts, and budget performance
Software development experience in any language
AI experience — using AI tools to accelerate analysis, generate documentation, or enhance reporting workflows
Microsoft PL-300 (Power BI Data Analyst) certification

Responsibilities

Design, build, and publish Power BI dashboards and reports that provide clear, actionable visibility into project performance, operational metrics, and financial data
Own the visual design and user experience of reports — making dashboards that are intuitive and clean
Identify gaps or issues in the data and communicate them back to the Analytics Engineering team for resolution at the pipeline or model level
Partner with operations leaders, project finance teams, and department heads to gather reporting requirements and translate business questions into well-defined data needs
Work closely with the Analytics Engineering team to produce highly curated reports and dashboards
Validate reports against source data and business logic — ensuring accuracy, consistency, and trustworthiness before reports reach end users
Support report adoption across the organization — training end users, gathering feedback, and iterating toward solutions that stick
Maintain thorough documentation for all reports, datasets, and KPI definitions so the business has a single source of truth for how metrics are calculated
Manage the report development lifecycle using SDLC and ALM practices — versioning, workspace governance, and controlled deployments