Director of Business Intelligence, Metropolis

• You are an organizational architect with a track record of building high-performing, multi-disciplinary data teams from scratch — engineers, data scientists, and analysts — and shaping the data culture of the organizations you’ve led
• You operate comfortably at the intersection of C-suite Finance strategy and hands-on quantitative analysis — translating the CFO’s most pressing questions into a multi-year roadmap and the team to deliver it
• You are a builder who thrives on complexity across systems, stakeholders, and business cycles, and who never loses sight of what matters most: trustworthy data and intelligence that drives better decisions, faster
• 10+ years in Data Engineering, Business Intelligence, Data Science, or Financial Technology, including 4+ years leading data teams and building organizations from the ground up, with a path to managing managers as the team scales
• Track record of building and scaling a multi-disciplinary data function at a high-growth technology or operations-intensive company
• Executive presence with fluent data storytelling skills to connect complex quantitative findings directly to business action
• Technical foundation in the modern Finance data stack (Snowflake, dbt, Airflow, Spark, Looker/Tableau) and cloud platforms (AWS or GCP), alongside statistical modeling and predictive analytics fluency
• Analytical depth and quantitative rigor in model validation, forecasting accuracy, statistical significance, and hypothesis-driven analysis
• Proven ability to drive lasting data governance and quality programs across systems and business cycles
• Track record of building AI/ML-augmented finance analytics including anomaly detection, intelligent forecasting, and automated variance analysis

Desirable

• Metropolis is seeking a Director, Business Intelligence – Finance to own the vision, strategy, and execution of Metropolis’s Business Intelligence function
• Own the Finance Business Intelligence strategy by setting the multi-year vision to build, govern, and scale the finance data environment from pipeline architecture to self-serve analytics and board-level reporting
• Hire and develop the function’s first BIEs, data scientists, and analysts, building toward a high-performing, multi-disciplinary team
• Evolve Finance analytics from reporting to intelligence by developing predictive modeling, AI-powered anomaly detection, driver-based forecasting, and scenario simulation
• Serve as the executive-level data partner to the Finance organization, translating strategic priorities into data infrastructure investments
• Design and govern the intake, prioritization, and delivery framework for all Finance data work to operate as a high-velocity, trusted product team
• Drive company-wide Finance data governance by establishing policies, standards, and ownership models that make metrics authoritative, discoverable, and auditable
• Evaluate and select tools, platforms, and integrations for the Finance data stack in partnership with the CTO and Data Platform team