Principal Data Engineer

Principal Data Engineer

Join Hims & Hers as a Principal Data Engineer to define and drive the architectural vision for the data platform in alignment with business goals. You’ll set technical standards across the systems you own, make high-stakes platform decisions, and lead incident response for critical data platform issues.

Key missions

• Define & align the data platform architecture vision with product, engineering, and data science leadership.
• Establish and enforce engineering standards and production readiness criteria across DPE-owned systems, including:
  • test requirements
  • CI/CD patterns
  • schema registry governance
• Technical ownership for cross-system changes impacting multiple systems and costs.
• Lead incident response for P1/P2 platform incidents, including systemic improvements.

Responsibilities & requirements

• Cloud-native data platform leadership with GCP primary (strong focus on BigQuery, GCS, Dataflow), plus operational familiarity with AWS (e.g., EKS-based Airflow).
• BigQuery strongly preferred; multi-cloud fluency required.
• Define and align architecture with business goals across an engineering organization.
• Data governance & compliance in regulated environments, including HIPAA/PHI handling and GDPR (data classification, access controls, audit logging).
• Design and operate event streaming pipelines at scale, including Schema Registry, data contracts, and consumer lag management.
• Data quality frameworks ownership (e.g., dbt testing, anomaly detection, schema validation, data observability).
• Establish engineering standards and drive adoption without direct authority.
• Infrastructure-as-Code fluency (e.g., Terraform), treating infra changes like software changes.
• Lead incident response and perform blameless RCA with systemic root cause identification.
• Hands-on modern data stack experience, including:
  • dbt at platform scale
  • Airflow/Astronomer
  • Kafka/Confluent
  • Databricks/Spark
  • Fivetran
  • data sharing/activation platforms (e.g., Hightouch)
• Strong Python and SQL skills for production-grade pipeline code.
• Produce alignment-focused design docs and RFCs; comfortable operating in ambiguity.

Nice-to-haves / additional signals

• 15+ years designing/building/owning data platform architecture at company scale.
• Experience with HIPAA + GDPR in direct-to-consumer healthcare/telehealth.
• Production experience with Databricks, Unity Catalog, Delta Lake.
• Familiarity with SOX compliance controls in data engineering.
• PySpark/SparkSQL for batch and streaming workloads.
• Experience migrating BigQuery → Databricks Lakehouse (or equivalent).
• MLOps partnership with ML engineers (feature stores, experimentation infra).
• CDC patterns and Flink for real-time processing.
• Service development in Go or Python for Kafka producers/consumers.

Location

• Full remote