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
