Director of Data & Analytics

Responsibilities

• Build & Lead the Team
• Lead and grow the data and analytics engineering team.
• Set the standard for rigor and data-driven decisions, and hold the team to it.
• Build the capacity and process that scale as the company grows.
• Data Platform & Architecture
• Own the design and build of Kipu’s data platform: the warehouse, the ingestion pipelines, and the transformation layers.
• The platform runs on Databricks and Azure.
• Set the standards for data modeling, pipeline reliability, and data quality.
• Make the decisions on the data stack: ELT, transformation, orchestration, and observability.
• Partner with Engineering and Business Systems on data contracts and source-system quality.
• Own the Partner Relationship
• Own the relationship with our outside data partner and everything they deliver.
• Treat the partner as an extension of the team, and hold their work to the same standard as internal work.
• Understand how everything they build works, so Kipu can run, support, and extend it independently.
• Bring knowledge and ownership in-house over time, so the platform does not depend on any single outside firm.
• We continue to use the partner by choice, not necessity.
• Analytics & Insight
• Build the analytics and reporting layer that every team relies on, in Power BI.
• Turn business questions into clear dashboards and analysis that teams rely on.
• Move teams to self-serve analytics so they can answer their own questions directly.
• Data Governance & Quality
• Set and enforce governance: definitions, ownership, lineage, and access controls.
• Build the data quality framework so the business trusts the numbers.
• Meet HIPAA requirements for how the platform handles data: access controls, audit trails, and least-privilege access.
• Stakeholder Partnership
• Be the person leadership turns to for what the data says and what it means.
• Translate an unstructured business question into a clear analytical answer, then translate the answer back into plain language.
• Make data accessible across the company, so teams can find answers themselves.

Requirements

• Must Have:
• 8+ years in data and analytics, with 3+ years leading a data or analytics team.
• You have designed and operated a modern data platform from ingestion through reporting.
• Strong SQL and hands-on data modeling.
• You have built a warehouse and the dimensional models beneath it.
• Strong command of ELT, orchestration, and pipeline reliability.
• You have owned a BI and visualization layer and driven its adoption across teams.
• Strongly Preferred:
• Databricks and Azure, where our platform runs.
• Power BI, our reporting tool.
• dbt or similar transformation tooling.
• Nice to Have:
• SaaS or high-growth company experience.
• Healthcare or behavioral health, where HIPAA and PHI shape how you handle data.