Staff Data Engineer

Staff Data Engineer

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 and hims.com/how-it-works.

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 ambiguous requirements, write clear solution designs, and ship to production with minimal rework

Preferred Qualifications:

• PySpark/SparkSQL for large-scale data processing

• Experience with Hightouch or equivalent reverse ETL platform

• Experience with MLOps - supporting ML engineers with data pipelines for model training, feature stores, or experimentation

• Familiarity with Looker LookML or equivalent BI serving layer

• Go experience for Kafka service development

• Experience at a direct-to-consumer healthcare, telehealth, or similarly regulated company

• Familiarity with UK/GDPR data compliance requirements distinct from US HIPAA

Our Benefits (there are more but here are some highlights):

• Competitive salary & equity compensation for full-time roles

• Unlimited PTO, company holidays, and quarterly mental health days

• Comprehensive health benefits including medical, dental & vision, and parental leave

• Employee Stock Purchase Program (ESPP)

• 401k benefits with employer matching contribution

• Offsite team retreats

We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. If you're excited about this role, we encourage you to apply—even if you're not sure if your background or experience is a perfect match.

Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at View email address on click.appcast.io and describe the needed accommodation. Your privacy is important to us, and any information