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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.
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.
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
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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
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
Publicly traded U.S. telehealth platform connecting consumers with licensed providers and personalized prescription and wellness care.
Visit company websiteJobs and hiring trendsUSD 170000-200000 yearly / year
Full-time
Senior · 8+ years experience
Remote
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