Senior Business Intelligence & Automation Analyst

About the role

The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required.

What You'll Do

• Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance.
• Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on.
• Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored.
• Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them.
• Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting.
• Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself.
• Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work.
• Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time.
• Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets.
• Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers.
• Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership.
• Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity.
• Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses.
• Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards.
• Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it.
• Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting.

Qualifications

• Education: Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, Information Systems, or a related quantitative field, or equivalent experience. Advanced degree preferred.
• Experience: 7+ years of experience as a Business Intelligence Engineer, Data Analyst, Analytics Engineer, Data Engineer, or a related occupation delivering BI, analytics, and reporting solutions. Fewer years required if candidate holds a relevant Master's qualification.
• Deep SQL proficiency and strong knowledge of data design and data modeling.
• Expert-level dashboard development in Power BI (or equivalent) for executive audiences.
• Experience programming to extract, transform, and clean large datasets from multiple, disparate sources, including raw and manually maintained data.
• Experience designing and implementing custom, automated reporting systems using automation and scripting tools such as Python and Power Automate.
• Track record of developing and monitoring KPIs to drive business decisions, ideally including benefit or value-realization tracking for strategic programs.
• Demonstrated ability to establish business logic and metric definitions that turn raw data into trusted, consumable reporting.
• Experience communicating and presenting analytical results to senior leadership, in writing and in person.

Skills & Attributes

• Builder's mindset: Takes loosely defined problems, works out the business intent behind them, and delivers working solutions end to end: requirements, data model, pipeline, dashboard, adoption.
• Comfort with ambiguity: Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker.
• Business acumen and financial literacy: Understands core finance concepts—ROI, forecasting, variance-to-plan, business-case logic—well enough to hold their own in a finance conversation. Has worked directly with a finance or FP&A team and can translate between data and business needs.
• Standalone technical IC: Comfortable being the only builder in the room, owning decisions end to end, with no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting.
• KPI and automation track record: Has developed and monitored KPIs that drive business decisions and built automated reporting systems that replaced manual processes.
• Executive presence: Experience communicating and presenting analytical results to senior leadership.
• Ownership and judgment: Validates own outputs, makes pragmatic build-versus-reuse trade-offs, and earns trust by being right about the numbers.
• Organization and prioritization: Manages multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip.
• Curiosity about AI: Interested in applying GenAI and agents to reporting; ideally has already experimented with them.

Technical Skills

• SQL: Expert-level complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. Writes queries that need little post-processing.
• Data modeling and design: Dimensional and star-schema modeling, semantic model design, and harmonized dataset construction. Can evaluate an end-to-end data design for its strengths and weaknesses.
• BI and visualization: Advanced Power BI and Tableau, including data modeling, DAX, executive-grade dashboards, and workspace and access management.
• ETL/ELT and pipelines: Hands-on experience programming to extract, transform, and clean large datasets, and building scheduled, monitored pipelines in tools such as Databricks, Microsoft Fabric, Azure Data Factory, or Snowflake.
• Scripting for automation: Proficiency in Python or a similar language for data transformation and automation.
• Workflow automation: Power Automate, Power Apps, or comparable low-code tooling for reporting workflows. Exposure to modernizing legacy RPA into AI-enabled solutions is a plus.
• Analytics foundations: Descriptive statistics, trend and variance analysis, and metric calibration, plus enough familiarity with inferential methods to know when to use them.
• AI-enabled analytics (differentiator): Applying LLM and GenAI capabilities to BI: automated narrative generation, conversational analytics, and agent-ready semantic layers.
• Executive tooling: Advanced Excel and PowerPoint for analysis and executive storytelling.