Director of Engineering, Data

Allara is hiring a Director of Data to build and lead its data function, starting with hands-on improvements to ETL pipelines, data models, and data quality. The role will own data strategy, governance, the shared data platform, and the growth of the data engineering team.

Responsibilities:

• Clean up the pipelines. Audit our existing ETL across Fivetran and Mozart into Snowflake, stabilize reliability and freshness, and fix the brittle parts the business has learned to work around
• Consolidate duplication. Collapse duplicated models, metrics, and transformation logic into a single, well-documented modeling layer, so there is one definition of each number rather than several that disagree
• Close source-data gaps. Map what we collect against what the business needs and close the gaps across our systems
• Make the data trustworthy. Stand up data-quality testing, monitoring, and alerting
• Establish one source of truth. Define a canonical metric and semantic layer
• Own the data strategy. Shape how Allara collects, models, governs, and uses data as the company scales, and advises leadership on tooling, investments, and build-versus-buy decisions
• Own governance and compliance. Own data governance, access control, and PHI and PII handling appropriate for a HIPAA-covered healthcare environment
• Own the shared platform. Serve departmental stakeholders and data analysts, as the owner of the platform and standards they build on, and enable trustworthy self-serve analytics
• Own AI-ready data. Own the shared, AI-ready data layer and the canonical terminology definitions and skills that power AI-assisted analysis across departments
• Build the team. Hire, mentor, and lead the data engineering function over time, setting the technical bar and the practices the team works by

Requirements:

• 8+ years in data engineering or analytics engineering, including direct, recent ownership of production ETL and warehouse modeling
• Strong SQL and a cloud warehouse (Snowflake preferred), ETL tooling, and a transformation and modeling layer
• A proven track record of taking over brittle, duplicated, or undocumented pipelines and turning them into reliable, documented, trusted data
• Strong data modeling fundamentals and a real bias toward a single source of truth
• Experience designing data governance and handling sensitive data, with comfort around security and access control in a regulated environment
• Healthcare or HIPAA experience, including familiarity with EMR data (FHIR) and claims
• Experience with D2C growth metrics
• Experience with Amplitude and product event taxonomy, and enabling AI or LLM-assisted analytics such as semantic layers, metric catalogs, or Claude skills
• Experience building and managing a data team at a high-growth startup (Series B to D)