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Hims & Hers, a NYSE-traded telehealth and wellness platform serving millions of patients, is seeking a Staff Data Engineer to join the Data Platform Engineering team. This is a hands-on technical leadership role spanning multiple squads, where you will drive architectural decisions, enhance cross-team reliability, and improve developer experience for nine engineers building the infrastructure powering patient care.
You will own large, complex deliverables end-to-end across the full data stack: BigQuery, dbt, Airflow on Astronomer, Confluent Kafka, Databricks, Fivetran, and Terraform/OpenTofu. As the DRI (Directly Responsible Individual) for cross-squad initiatives, you will be the engineer other Senior Data Engineers look to for technical direction and mentorship.
Key responsibilities include: serving as DRI for high-complexity, multi-sprint platform initiatives (Fivetran connector buildouts, Databricks Lakehouse migrations, event streaming infrastructure); architecting and maintaining production-grade ingestion pipelines and platform infrastructure from source connectivity through Bronze/Silver layers; designing and operating event-driven streaming pipelines using Kafka, PySpark, and Databricks Structured Streaming with defined scaling strategies and cost guardrails; owning data contracts, schema governance, and SLAs for ingestion and raw-to-cleansed layers; implementing data quality gates including dbt tests, anomaly detection, and schema validation; establishing KPIs and SLOs with Datadog monitoring and on-call participation; managing Fivetran connectors and Hightouch reverse ETL pipelines end-to-end; supporting Analytics Engineers and Data Scientists by building platform capabilities; identifying and resolving systemic inefficiencies; mentoring Senior Data Engineers through design and code reviews; and driving adoption of engineering standards across the organization.
Required qualifications: 8+ years designing, building, and operating data pipelines and platform infrastructure; hands-on experience with CDC patterns, Flink stream processing, and dbt governance in production BigQuery or Databricks environments; proven ability building and operating Airflow DAGs at scale; experience with Kafka/Confluent Kafka for event streaming; multi-cloud fluency across GCP and AWS; data quality ownership experience; Fivetran or equivalent connector platform experience; Databricks platform expertise including Delta Lake and Unity Catalog; familiarity with HIPAA/PHI compliance in regulated environments; Infrastructure-as-Code with Terraform; and strong Python and SQL skills.
