Head of Data

Seen Health

$120K — $180K *
US-Anywhere
+ 2 other locationsRemote
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in data engineering and architecture.
  • Proficient in SQL and Python, with hands-on experience in modern data stacks such as dbt and BigQuery.
  • Demonstrated end-to-end ownership of a data system, including architecture and maintenance.
  • Experience with AI tools for code generation and automation.
  • Strong problem-solving skills and ability to manage evolving objectives.
  • Passionate about supporting healthcare for vulnerable populations.

Responsibilities

  • Architect and manage the entire AI-native data stack, ensuring quality and efficiency.
  • Develop and maintain reliable data pipelines for diverse healthcare data sources.
  • Design pathways for structured and unstructured data integration across various systems.
  • Establish a comprehensive metadata layer to standardize data definitions for the organization.
  • Create actionable metrics and insights for various stakeholders to enhance decision-making.
  • Oversee analytics related to risk adjustment and clinical performance.
  • Lead the data team in setting the data roadmap, quality standards, and ensuring data security.

Benefits

  • Relocation assistance available for candidates moving to San Francisco or Los Angeles.
  • Opportunity to participate in company equity and stock options.
  • Flexible remote work arrangements with quarterly in-person meetings.
Full Job Description
Why this role

We are the payer, provider, and tech team, so we sit on something almost no healthcare company has: clinical, claims, financial, and operational data across the entire system, in one place, from day one. You will own that entire data stack as a founding member of the team. You are responsible for building and evolving the data engine at the core of our operations. You get to build the data platform, the intelligence layers on top, and the culture of data-driven decision making in one of the most complex and effective models of healthcare.
What you'll own
  • AI-native data engineering: architect the whole data stack - ingestion, orchestration, warehouse, transformation, and analytics - and direct a fleet of AI agents to build and maintain it. You set the architecture, engineering practices, and quality bar; agents do almost 100% of coding
  • Own the pipelines that reliably move clinical (FHIR/EHR), claims (EDI 837/834/820), pharmacy, financial, operational, and internal data through Dagster, dbt, and BigQuery
  • Build new pathways for data in and out, structured and unstructured: state and payer feeds, vendor SFTP drops, partner APIs, regulatory exports, CMS audit deliverables, plus call recordings, visit notes, faxes, and scanned records that live outside any system of record today
  • Build and evolve a metadata layer that guides humans and agents: a catalog of what data exists and what it means, and a semantic layer on top so every dashboard, analyst, and agent is querying the same definition of "member," "risk score," and "cost of care"
  • Turn data into decisions: ship the metrics, dashboards, and insights that clinicians, operators, finance, and regulators rely on; measure success in decisions made faster and outcomes improved
  • Own the analytics behind risk adjustment and clinical quality: HCC/RAF capture, care gap closure, quality measure reporting, and the burden-of-illness view that connects clinical documentation to financial performance
  • Build the intelligence layer for the company: capture what happens on every call, visit, and meeting through agents and recordings, and turn it into structured signal instead of knowledge that lives in someone's head - then use it to give leadership proactive, org-level visibility into what's breaking before anyone has to ask
  • Lead the data team: hire and manage a mix of internal and external resources, set data roadmap, quality standards, and PHI/security posture
Must-haves
  • Exceptional talent and trajectory: we optimize for slope, not years
  • Deep fluency in SQL and Python, plus the modern data stack: dbt, an orchestrator (e.g. Dagster), a cloud warehouse (e.g. BigQuery), infrastructure-as-code (e.g. Terraform), cloud storage (e.g. GCS), and BI (e.g. Metabase)
  • End-to-end ownership of a 0 1 1 data system: you've architected it, shipped it, and answered for it when it broke
  • AI-native way of working: agents (Claude Code, Codex, or similar) are already your primary way of building, and you know how to direct, review, and verify their work
  • Bias for action, pragmatism, and comfort with ambiguity and evolving objectives, including direct iteration with non-technical users
  • Energized by standing shoulder-to-shoulder with clinicians serving vulnerable elders
Nice-to-haves
  • Healthcare data experience: FHIR/HL7, EDI claims and enrollment files, risk adjustment (HCC/RAF), eligibility, pdf ingestion
  • Event-driven and streaming ingestion patterns, CDC
  • Security-by-design mindset and HIPAA/PHI compliance experience
  • Mandarin, Cantonese proficiency
How we work

Small senior crew 1 Ship daily 1 Automate everything 1 2uild > complain2 1 Remote with at least quarterly visits to our center.
Location
  • San Francisco or Los Angeles ideal.
  • Relocation benefits available.
Salary & Benefits
  • Salary is competitive and includes benefits.
  • Participation in company equity/stock included.

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