Senior Data Engineer

Founding Data Engineer — AI HealthcareOur client is building an AI-powered healthcare platform designed to make high-quality care more accessible at massive scale.They're now hiring their first dedicated Data Engineer to build the data foundation behind the company.This is not a role where you inherit a mature platform and optimize around the edges.You'll own how data moves through the business from end to end — from production systems into the lakehouse and warehouse, through transformation and governance, and ultimately into the hands of AI, product, finance, partnerships, and leadership.If you've wanted the opportunity to define how a company thinks about data from the ground up, this is it.What You'll OwnBuild the Data PlatformDesign and operate reliable CDC and ELT pipelines from MariaDB, PostgreSQL, and MongoDB into S3, Apache Iceberg, and SnowflakeCreate a governed, trusted source of production data that the entire company can build onDesign a scalable warehouse architecture with clean raw, transformed, and business-ready layersImplement monitoring, alerting, and reliability standards across the data stackCreate Trusted Business DataBuild the transformation layer using dbt or similar toolingTurn raw production data into tested, documented, version-controlled modelsEstablish trusted definitions for metrics such as:VisitsBookingsRevenueRetentionProduct engagementPower executive reporting and downstream analytics from a consistent source of truthOwn Orchestration & ReliabilitySelect and implement the right orchestration platform for the companyAutomate pipelines, transformations, and dashboard refreshesBuild monitoring and alerting so failures are caught quicklyEstablish reliability standards as the volume and complexity of the platform growsBuild Healthcare-Grade Data GovernanceRow- and column-level access controlsPHI restrictionsHIPAA-aligned data architectureSafe Harbor anonymizationData deletion workflowsRole-based access policiesSecure datasets for analytics and AI use casesThe goal is to make data highly useful without compromising patient privacy or security.Enable AI & Product TeamsBuild datasets and pipelines supporting AI model training and evaluationPartner with AI engineers on training data and data qualitySupport product teams with trustworthy behavioral and product dataHelp finance, marketing, partnerships, and leadership answer important business questions without creating separate versions of the truthWhat We're Looking For5+ years of data engineering experienceExperience owning production data infrastructure end to endStrong SQL and PythonExperience building and maintaining CDC / ELT pipelinesFamiliarity with tools such as Fivetran, Airbyte, or similar platformsHands-on experience with modern warehouse or lakehouse architecturesExperience with:AWS S3Apache IcebergSnowflake or similar data warehousesData catalogsdbt or comparable transformation frameworksExperience with orchestration platforms such as Airflow, Dagster, or AWS GlueStrong AWS fundamentals including IAM, Lambda, Kinesis, and GlueStrong understanding of production reliability and data qualityThe Type of Engineer Who Thrives HereThis role is best suited for someone who:Likes building systems from scratchDoesn't need a perfectly defined roadmap before getting startedCan evaluate tools rather than simply use whatever is already installedThinks about reliability, governance, and maintainability from day oneCan translate business questions into durable data modelsCommunicates well with technical and non-technical stakeholdersWants meaningful ownership instead of narrowly scoped ticketsEnjoys being the person people turn to when the answer starts with, "What does the data actually say?"Particularly Relevant ExperienceExperience in any of the following would be especially valuable:HIPAA, PHI, or healthcare dataHealthcare technologyData anonymization and governanceML training datasets and feature pipelinesSageMaker, Databricks, or Jupyter environmentsClickHouse or high-volume event pipelinesServer-side tracking, CDPs, or behavioral analyticsBI tooling such as MetabaseSemantic or metrics layersFirst data engineer or early-stage startup experienceHealthcare experience is helpful, but the bigger requirement is that you've built reliable, governed data infrastructure in production.Why This RoleYou'll have an unusually broad mandate.Your work will directly influence:How the company measures performanceHow executives make decisionsHow AI models are trainedHow patient data is protectedHow product teams understand behaviorHow the company scales its analytics infrastructureInstead of joining a large data organization and owning one piece of the stack, you'll have the opportunity to design the stack itself.CompensationBase Salary: $200,000 – $275,000Equity: Meaningful ownership based on experience and levelThis is an opportunity to become the technical owner of the data foundation behind a rapidly scaling AI healthcare company.