Staff Data Engineer

Role Overview

Join Hims & Hers as a Staff Data Engineer, driving critical platform data initiatives across multiple squads. You’ll own complex deliverables end-to-end, architect and maintain production ingestion pipelines, and improve cross-team reliability and the developer experience.

Key Missions

• Make shared architectural decisions to improve inter-team reliability and overall developer experience.
• Own large, complex deliverables from design through production.
• Ensure data quality and system reliability for production pipelines.
• Mentor Senior Data Engineers via design reviews, code reviews, and pairing.
• Help adopt and reinforce engineering standards.

Responsibilities

• Architect, build, and operate production-grade ingestion pipelines.
• Lead event streaming and orchestration for reliable data movement.
• Govern and administer dbt in production (BigQuery and/or Databricks).
• Implement monitoring, alerting, and governance for schema changes and data drift.
• Apply data compliance practices appropriate for regulated healthcare environments.
• Contribute to CI/CD, testing, and documentation standards for the data platform.

Requirements

• 8+ years designing, building, and operating data pipelines and data platform infrastructure.
• Strong Python and SQL skills for production-grade pipeline development.
• Kafka/Confluent Kafka event streaming experience (producers/consumers, schema evolution, Schema Registry governance, consumer lag management).
• Databricks experience.
• Delta Lake, Databricks Workflows, and Unity Catalog.
• Airflow at scale (DAG reliability, task-level orchestration patterns, multi-priority scheduling) with orchestration on AWS EKS.
• BigQuery (data platform on GCP) and ingestion-layer work with dbt (Bronze/Silver).
• Terraform (or equivalent IaC) with infrastructure changes treated as code.
• Data quality ownership for production pipelines (dbt tests, anomaly detection, alerting on schema changes and data drift).
• CI/CD configuration, testing standards, documentation standards, and schema governance.
• Multi-cloud fluency across GCP and AWS.

Additional Skills / Nice-to-Haves

• Flink for stream processing.
• Spark/PySpark/SparkSQL for large-scale processing.
• CDC (Change Data Capture) for real-time ingestion.
• Fivetran (or equivalent connector platform), connector health monitoring, schema change handling.
• Hightouch (or equivalent reverse ETL platform).
• MLOps experience supporting ML data pipelines (feature stores, training data, experimentation).
• Looker LookML (or equivalent BI serving layer).
• Go experience for Kafka service development.
• Experience in direct-to-consumer healthcare/telehealth or similarly regulated settings.
• Familiarity with UK/GDPR compliance distinct from US HIPAA.
• HIPAA/PHI handling, access controls, and audit logging.