Staff Data Engineer

About this role

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve. 

Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit hims.com/about http://hims.com/about and hims.com/how-it-works http://hims.com/how-it-works . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals http://www.hims.com/careers-professionals.

ABOUT THE ROLE:

We're looking for a Staff Data Engineer to join the Data Platform Engineering team at Hims & Hers as a key technical driver for our most critical platform initiatives. Your scope spans multiple squads: you will drive shared architectural decisions, enhance cross-team reliability, and improve the overall developer experience for a team of nine engineers building the infrastructure that powers patient care for millions of Hims & Hers subscribers.

This is a hands-on execution role. You will own large, complex deliverables end-to-end - from design through production - across our full stack: BigQuery, dbt, Airflow on Astronomer, Confluent Kafka, Databricks, Fivetran, and Terraform/OpenTofu. You will be the DRI (Directly Responsible Individual) for cross-squad initiatives and the engineer other Senior DEs look to for technical direction and growth.

YOU WILL:

- Serve as DRI for high-complexity, multi-sprint platform initiatives - Fivetran connector buildouts, Databricks Lakehouse migration workstreams, event streaming infrastructure, lower environment implementation, and engineering standards adoption

- Architect, build, and maintain production-grade ingestion pipelines and platform infrastructure - from source connectivity through Bronze/Silver layers - that Analytics Engineering, Data Science, and business teams build on daily

- Design, implement, and operate event-driven and streaming data pipelines using Kafka, PySpark, and Databricks Structured Streaming - including defining scaling strategies, cost guardrails, consumer lag alerting, and runbooks before those services reach production

- Own the ingestion and raw-to-cleansed layer (Bronze to Silver) data contracts, schema governance, and SLAs

- Own data quality for pipelines you build: write dbt tests, wire anomaly detection, validate schemas, and alert on data drift - pipelines ship with quality gates, not after them

- Own the reliability of systems you build: establish KPIs and SLOs, implement Datadog monitoring and alerting as code, participate in the on-call rotation, and own Tier 1 operational tickets and runbooks for systems under your domain

- Own the integration and data activation layer - Fivetran connectors and Hightouch reverse ETL pipeline connectors - end-to-end from IaC provisioning to production monitoring and schema change governance

- Support Analytics Engineers, Data Scientists, and ML engineers by building platform capabilities and data pipelines that unblock their roadmap; partner with legal, security, and DevOps on compliance controls and IaC hardening as needed. DE's responsibility is the platform layer and data delivery; transformation logic and model readiness for serving are owned by Analytics Engineering

- Identify and resolve systemic inefficiencies across DPE-owned pipelines and infrastructure - root cause, not just symptom

- Mentor Senior Data Engineers through design reviews, code reviews, and pairing; help them grow from squad-level to cross-squad scope

- Contribute to and drive adoption of engineering standards - testing practices, CI/CD patterns, observability-as-code, Schema Registry governance - and participate in ARC reviews for changes with cross-team or cost impact

YOU HAVE:

- 8+ years of professional experience designing, building, and operating data pipelines and platform infrastructure

- Experience with CDC (Change Data Capture) patterns for real-time ingestion.

- Experience with Flink for stream processing

- Experience governing and administering dbt in a production BigQuery or Databricks environment - CI/CD configuration, testing standards, documentation standards, and platform-level schema governance. Hands-on dbt experience for ingestion-layer (Bronze/Silver) pipelines

- Experience building and operating Airflow DAGs at scale - task-level orchestration patterns, DAG reliability, and multi-priority scheduling

- Experience building event streaming pipelines using Kafka or Confluent Kafka - producers, consumers, schema evolution, Schema Registry governance, and consumer lag management

- Multi-cloud fluency across GCP and AWS - both are required day-to-day: BigQuery runs on GCP, Airflow runs on AWS EKS

- Experience owning data quality for production pipelines - dbt tests, anomaly detection, alerting on schema changes and data drift

- Experience with Fivetran or equivalent connector platform - IaC provisioning, schema change handling, and connector health monitoring

- Experience with the Databricks platform - Delta Lake, Databricks Workflows, and Unity Catalog

- Familiarity with data compliance in a regulated environment - HIPAA/PHI handling, access controls, and audit logging

- Infrastructure-as-code experience - Terraform or equivalent; you treat infrastructure changes like code changes

- Strong Python and SQL skills; comfortable writing, reviewing, and raising the bar on production-grade pipeline code

- Strong design instincts: you take ambiguo

Similar jobs

• Staff Data Engineer — Xometry · Waltham, MA
• Staff Data Engineer — Clickup · Remote
• Staff Data Engineer — Onxmaps · Bozeman, Montana, United States
• Staff Data Engineer — Verkada · San Mateo, CA United States
• Staff Data Engineer — Artisan · San Francisco
• Staff Data Engineer — Oxio · Remote
• Staff Data Engineer — Crunchyroll · Los Angeles, California, United States
• Staff Data Engineer — Jellyfish · Remote