Power BI Engineer

Senior Business Intelligence Engineer (Power BI) Experience level: 5+ years Function: Data & Analytics / Business Intelligence Engagement type: Client-facing delivery (consulting / embedded analytics) About the Role We're looking for a Senior BI Engineer who can own the full lifecycle of analytics delivery, from data modeling in the warehouse through to polished, secure, production-grade Power BI reporting embedded in client-facing applications. This is a hybrid technical and consultative role. You'll build the reports, engineer the data behind them, and communicate directly with client stakeholders about priorities, trade-offs, and progress. You'll work on a mature analytics program spanning executive dashboards, member/partner performance reporting, geospatial analytics, embedded portal analytics, and emerging AI-driven conversational analytics. The right person is equally comfortable debugging a row-level security conflict in DAX, tuning a Snowflake view, and explaining a data limitation to a non-technical business owner in plain language. What You'll Do • Design, build, and maintain Power BI reports and dashboards, from data model through DAX measures to final layout and interactivity. • Implement and troubleshoot row-level security (RLS), including dynamic/organization-scoped security and its interaction with export, embedding, and cross-group comparison logic. • Develop robust semantic models using Power Query / M and DAX, with attention to performance, maintainability, and correctness under security filters. • Build and support embedded analytics delivered through a partner/portal web application (Power BI Embedded), including effective-identity token handling. • Engineer and optimize the data layer in Snowflake, writing SQL, building and debugging views, and diagnosing hidden dependencies such as masking policies, row-access policies, and view lineage. • Integrate external and third-party data sources (e.g., public datasets, government/nonprofit APIs, demographic and geospatial data) into the warehouse and reporting layer, including handling API versioning and schema changes over time. • Build geospatial visuals, including map layers and reference geometries, and work through platform constraints such as feature caps, boundary data quality, and geocoding issues. • Contribute to AI-assisted analytics initiatives (e.g., conversational/natural-language analytics over governed datasets). • Own data validation and UAT for new pipelines and reports, verifying correctness across raw, curated, and reporting layers before and after release. • Support data governance practices, including data cataloging and documentation, and identifying and handling sensitive/PII data appropriately. • Translate business requirements into technical specifications, and communicate status, blockers, and recommendations directly to client stakeholders in a clear, professional, conversational tone. • Produce clean documentation and work breakdowns; scope and estimate level of effort for new requests. Must-Have Qualifications • 5+ years of hands-on BI/analytics engineering experience, with a strong concentration in Power BI. • Expert-level DAX and Power Query / M, able to write, optimize, and debug complex measures and transformations. • Strong data modeling fundamentals (star schema, relationships, cardinality, and their impact on report behavior). • Deep, practical experience with row-level security in Power BI and its edge cases around export and embedding. • Advanced SQL (required) and solid experience with a cloud data warehouse. Snowflake strongly preferred (or Redshift/BigQuery/Synapse with willingness to ramp on Snowflake). • Python (required) for data work, including API integration, data prep/transformation, notebook-based workflows, and automation/scripting. • Solid grasp of data warehousing and ELT/ETL concepts and best practices. • Discipline around data validation, QA, and testing, plus awareness of data governance and sensitive/PII handling. • Experience delivering in a client-facing or stakeholder-facing capacity: gathering requirements, managing expectations, and explaining technical concepts to non-technical audiences. • Strong troubleshooting instincts, able to trace a reporting symptom back to a root cause in the data, the model, the security layer, or the source system. • Clear written and verbal communication; comfortable owning updates and coordinating across a delivery team. Nice-to-Have Qualifications • Power BI Embedded and Power BI Service administration (workspaces, deployment pipelines, capacity, gateways). • Experience with Snowflake Cortex or other LLM/AI-assisted analytics tooling. • Geospatial/mapping experience (Azure Maps, GeoJSON, geocoding, shapefiles/boundary data). • Familiarity with a modern cloud stack (AWS such as Lambda, S3, ECS/Fargate, EventBridge, CloudWatch, or Azure equivalents). • Database migration/versioning tooling (e.g., Liquibase), and source control workflows (Git/GitHub). • Experience integrating third-party or public APIs (demographic, government, or nonprofit-sector datasets). • Exposure to Streamlit, FastAPI, or similar for lightweight data applications and data-service APIs. • Familiarity with a second BI/visualization tool (e.g., Tableau). • Relevant certifications (e.g., Microsoft PL-300 / Power BI Data Analyst Associate, SnowPro). What Success Looks Like In the first few months, you'll take ownership of existing report workstreams, resolve outstanding issues independently (escalating with specific technical context and evidence when needed), and become a reliable point of contact the client trusts for both delivery and honest technical guidance. You'll leave the codebase, data models, and documentation in better shape than you found them. Key Competencies - Technical depth - Can diagnose problems across the full stack: report, model, security, warehouse, and source Data modeling - Builds performant, maintainable semantic models that behave correctly under RLS where applicable Communication - Speaks in a business-friendly way, staying technically precise when the audience calls for it; explains complex issues simply; adjusts tone to the audience Ownership - Investigates independently before escalating; follows through to root cause Judgment - Knows when to reword, when to preserve exact wording, and when to ask