Lead technical authority for Power BI reporting: design and govern semantic layer and data models, enforce BI standards and deployment practices, build complex executive dashboards with advanced DAX and Power Query, manage intake and mentor analysts, and partner with IT/Engineering on data sourcing and performance.
Bottom line: The Power BI Lead is the technical and architectural authority for all BI reporting across MCP/LOS. This person sets the standard - owns the semantic layer, governs the data model, mentors the analyst, and manages intake - while remaining hands-on building the most complex reports and dashboards. The role requires equal parts technical depth, design discipline, and stakeholder credibility across operations, IT/Engineering, and executive leadership.
CORE RESPONSIBILITIES
ARCHITECTURE & DATA MODEL
- Design and own the Power BI semantic layer (datasets, shared models, calculated measures)
- Define the strategy for sourcing data from both MCP/LOS directly and the data warehouse/mart
- Establish medallion or equivalent layering conventions for data freshness and reliability
- Govern gateway configuration, scheduled refresh, and performance optimization
GOVERNANCE & STANDARDS
- Define and enforce naming conventions, measure libraries, and report templates
- Own workspace organization, access control, and row-level security (RLS) patterns
- Establish version control and deployment pipeline practices (e.g., PBIP/Git)
- Maintain documentation standards for datasets, measures, and data lineage
HANDS-ON DEVELOPMENT
- Build and own the most complex reports - executive dashboards, KPI scorecards, regulatory outputs
- Write advanced DAX for complex time intelligence, ratios, and dynamic filtering
- Design Power Query/M transformations from both MCP DB and warehouse sources
- Review and approve analyst-produced reports before publishing to business stakeholders
TEAM & INTAKE
- Manage and prioritize the BI request intake queue across all stakeholder groups
- Assign, scope, and review analyst work; provide technical mentorship
- Represent BI capability in cross-functional planning and project discussions
- Partner with IT/Engineering on data model changes that affect reporting
REQUIRED SKILLS
Technical
- Advanced Power BI Desktop - complex data models, composite models, DirectQuery
- Advanced DAX - time intelligence, iterators, context transition, dynamic measures
- Power Query / M - multi-source transformation, parameterization, error handling
- SQL proficiency - query optimization, joins, aggregations against relational DBs
- Familiarity with data warehouse concepts - star schema, slowly changing dimensions
- Power BI Service administration - workspaces, deployment pipelines, RLS, gateway
- Version control fundamentals (Git or equivalent)
Functional & Leadership
- Proven ability to define BI standards and enforce adoption across a team
- Experience designing executive-facing dashboards with clear KPI storytelling
- Mortgage/lending industry familiarity - pipeline metrics, pull-through, cycle time, regulatory reporting
- Ability to translate ambiguous business asks into structured analytical requirements
- Player/coach orientation - willing to stay hands-on while providing oversight
- Comfortable presenting to and defending design decisions with executive stakeholders
COMMUNICATION REQUIREMENTS BY STAKEHOLDER
Executive / Leadership
KPI dashboards, strategic reporting, intake prioritization discussions
- Present data clearly with business context - not just numbers, but meaning
- Manage expectations on what is and isn't measurable given data availability
- Defend design and methodology decisions concisely and with confidence
Internal Business / Operations
Requirements gathering, report delivery, training, issue resolution
- Translate user requests into structured data requirements without jargon
- Manage intake prioritization transparently - explain trade-offs clearly
- Deliver reports that are self-service where feasible, reducing dependency
IT / Engineering
Data model changes, source system access, warehouse/mart design collaboration
- Engage technically - able to discuss schema design, query performance, and data pipeline impacts
- Provide clear reporting requirements upstream so data is structured correctly at the source
- Flag reporting blockers caused by data quality or model gaps with specificity
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