Staff Data Engineer

About the role

Join Hims & Hers as a Staff Data Engineer, where you'll be a key technical driver for critical platform initiatives. You'll work across multiple squads, enhancing cross-team reliability and improving the overall developer experience. This hands-on role involves owning large, complex deliverables end-to-end, architecting and maintaining production-grade ingestion pipelines, and ensuring data quality and system reliability. You'll also mentor Senior Data Engineers and contribute to engineering standards adoption. Enjoy generous PTO, full healthcare coverage, retirement planning, and the flexibility to work from anywhere in the US. Key missions: Conduire des décisions architecturales partagées, améliorer la fiabilité inter-équipes et l'expérience développeur globale.. Posséder des livrables complexes de bout en bout, de la conception à la production, en utilisant des technologies telles que BigQuery, dbt, Airflow, Kafka, Databricks.. Mentorer les ingénieurs en données seniors à travers des revues de conception, des revues de code et des sessions de pairage. Profile: - Infrastructure-as-code experience - Terraform or equivalent; you treat infrastructure changes like code changes - Experience building event streaming pipelines using Kafka or Confluent Kafka - producers, consumers, schema evolution, Schema Registry governance, and consumer lag management - Experience with the Databricks platform - Delta Lake, Databricks Workflows, and Unity Catalog - 8+ years of professional experience designing, building, and operating data pipelines and platform infrastructure - Multi-cloud fluency across GCP and AWS - both are required day-to-day: BigQuery runs on GCP, Airflow runs on AWS EKS - Experience building and operating Airflow DAGs at scale - task-level orchestration patterns, DAG reliability, and multi-priority scheduling - Experience with Flink for stream processing - Experience owning data quality for production pipelines - dbt tests, anomaly detection, alerting on schema changes and data drift - 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 - Strong Python and SQL skills; comfortable writing, reviewing, and raising the bar on production-grade pipeline code - Familiarity with data compliance in a regulated environment - HIPAA/PHI handling, access controls, and audit logging - Strong design instincts: you take ambiguous requirements, write clear solution designs, and ship to production with minimal rework - Experience with Fivetran or equivalent connector platform - IaC provisioning, schema change handling, and connector health monitoring - Experience with CDC (Change Data Capture) patterns for real-time ingestion - Experience with Hightouch or equivalent reverse ETL platform - PySpark/SparkSQL for large-scale data processing - 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 - 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