POSITION SUMMARY
The Senior BI Analyst is the senior practitioner translating IGEN's Data Foundation into the governed dashboards, certified KPIs, and analytical insights that leadership and functional teams use to run the business. Owns the portfolio of executive and operational reporting in Power BI — including dataset modeling, KPI definition and certification, and the data product lifecycle from intake through retirement. Partners directly with executives across Technology, Product, Client Experience, Sales, and Marketing to convert business questions into trusted, repeatable analytics; mentors BI Analysts and contributes to the data literacy of the broader organization. Operates with AI-assisted analytical capabilities as a standard part of the discipline, builds within the broader Microsoft and Azure ecosystem, and supports IGEN's transition from anecdotal decision-making to data-driven decision-making as a cultural norm.

Preferred location for this position is our Corporate Headquarters in Appleton, WI, with hybrid work options available.

JOB RESPONSIBILITIES

• Leads the design and delivery of the executive reporting portfolio in Power BI — covering revenue, client health, product usage, filing performance, and operational throughput — replacing manual extraction with governed, live dashboards used in standard leadership reviews.
• Defines, certifies, and stewards business KPIs — including KPI definitions, source traces, calculation logic, owners, and certification status — and operates the governance forum that approves new KPIs and resolves definition disputes.
• Builds and maintains analytical solutions that support the Client Experience function — including operational KPI dashboards, the client health scoring model, exception reporting, and onboarding cycle-time analytics — partnering directly with CX leadership on data product roadmap.
• Delivers analytical solutions across business domains — including sales, marketing, customer, product, operations, and finance analytics — enabling functional teams to operate from governed data rather than ad hoc extracts. Example use cases include pipeline and win/loss reporting, customer health and engagement analytics, product usage by client segment, conversion patterns, and upsell / cross-sell targeting.
• Partners with the Senior Data Engineer and Data Engineers on data product requirements — including source data needs, transformation logic, refresh cadence, and SLA definition — ensuring the data foundation produces the inputs analytical solutions require.
• Uses AI development assistants — GitHub Copilot, Microsoft Copilot, Claude, and emerging agent-based tooling — as a standard part of daily analytical practice. Applies sound judgment in reviewing, validating, and securing AI-generated analytical logic, queries, and narrative output.
• Drives data literacy across the organization — through dashboard design that supports self-service exploration, structured training for business users, and partnership with the Director of Insight Engineering on the formal data literacy program for leadership and department heads.
• Mentors BI Analysts — through dashboard review, technique pairing, and knowledge sharing — and contributes to the growth of the team's analytical capability as IGEN scales the function.
• Manages stakeholder relationships across Technology, Product, Client Experience, Sales, and Marketing — running intake conversations, scoping work, presenting findings, and translating between business language and data language.
• Applies statistical methods to business analytics — including segmentation, trend analysis, distribution and outlier analysis, and forecasting — to surface insights that descriptive reporting alone cannot produce.
• Operates inside the AI governance framework developed in partnership with U.S. Venture Legal, InfoSec, Privacy, and Compliance — ensuring analytical work supports IGEN's SOC 2 Type 2 obligations and the responsible deployment of AI-assisted capabilities.
• Drives dashboard performance, refresh reliability, and cost management on the Power BI platform — including dataset optimization, incremental refresh strategy, and capacity governance.
• Continuously develops professionally — particularly in AI-assisted analytics, agentic analytical workflows, and emerging Microsoft and Azure analytics platform capabilities. Stays current as the boundary between human and agent work continues to evolve.
• Lives the company values of High Performance, Caring Relationships, Strategic Foresight, and Entrepreneurial Spirit. Champions continuous improvement and quality.
• Supports corporate efforts for safety, government compliance, and all other company policies and procedures
• Live our values of High Performance, Caring Relationships, Strategic Foresight, and Entrepreneurial Spirit
• Find A Better Way by championing continuous improvement and quality control efforts to identify opportunities to innovate and improve efficiency, accuracy, and standardization
• Continuously learn and develop self professionally
• Support corporate efforts for safety, government compliance, and all other company policies & procedures
• Perform other related duties as required and assigned

QUALIFICATIONS

Required:

• Bachelor's degree in Mathematics, Statistics, Computer Science, Economics, Information Systems, or related discipline; or equivalent demonstrated experience.
• 4-7 years of professional experience transforming large quantities of data into actionable insights presented to executive and cross-functional audiences.
• Advanced proficiency with an enterprise reporting and analytical platform — Power BI (preferred), Tableau, Qlik, Looker, ThoughtSpot, or equivalent — including dataset / semantic modeling, complex measure authoring (DAX or equivalent), row-level security, refresh management, and integration with modern data warehouses. IGEN is primarily a Power BI shop; Power BI fluency is expected on-the-job, and candidates without direct Power BI experience are expected to demonstrate strong fluency in an equivalent platform.
• Advanced proficiency in SQL — including complex query authoring, performance tuning, and querying against modern cloud data platforms (Snowflake preferred; Databricks, Azure Synapse, BigQuery, or equivalent also valued).
• Hands-on proficiency with Python for analytics — including data manipulation (pandas), exploratory analysis, and integration with analytical and visualization tooling.
• Hands-on experience using AI development assistants (GitHub Copilot, Microsoft Copilot, Claude, or equivalent) as part of daily analytical practice.
• Demonstrated experience defining, certifying, and stewarding business KPIs — including definition stewardship, source traceability, and governance facilitation.
• Working knowledge of statistical methods applied to business analytics — segmentation, trend analysis, distribution and outlier analysis, and forecasting.
• Strong foundation in data security, privacy, and governance — including data classification, access controls, and PII handling principles — with the ability to operate inside a regulated-data environment.
• Strong foundation in data modeling — conceptual and dimensional — and the ability to translate operational source data into analytical structures.
• Excellent written and verbal communication skills — including the ability to tailor analytical findings to executive, operational, and technical audiences.
• Strong stakeholder management skills — able to influence and align diverse stakeholders, build consensus on KPI definitions, and resolve scope and priority tradeoffs.
• Demonstrated ability to mentor and grow analytical talent.
• Comfortable operating in an agile, fast-moving environment with shifting priorities.

Preferred:

• Microsoft Power BI certification (PL-300 Data Analyst Associate), Azure data analytics certification, or vendor certification on an equivalent enterprise reporting platform.
• Direct experience with a modern cloud data platform — Snowflake (preferred), Databricks, Azure Synapse, BigQuery, or equivalent — including warehouse access, role-based access control, and query performance tuning.
• Experience with semantic-layer modeling tools (dbt Semantic Layer, Cube, or equivalent).
• Experience integrating analytics with AI/ML services — Azure OpenAI Service, Azure AI Foundry, embedding models, or vector database technologies.
• Experience building or operating client-facing analytics features inside a SaaS product.
• Experience working in regulated industries or with compliance-sensitive data (SOC 2 Type 2, SOX, financial data, regulated commerce).
• Experience with data catalog and metadata management tooling (Microsoft Purview, Atlan, Collibra, or equivalent).
• Familiarity with predictive modeling techniques and the boundary between business analytics and data science work.
• Experience contributing to or operating a data Center of Excellence — including intake processes, prioritization, and KPI governance.

DIVISION:

IGEN 91-00-800-0000