HH
$220,000 – $260,000
Listed on Hims and Hers’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Principal Data Engineer to architect Hims & Hers' multi-year data platform serving millions of patients, making foundational choices about streaming, governance, and self-service capabilities that other teams will build on for years. Ideal for someone who has shaped data infrastructure across organizations without direct reports, and wants to own the strategic decisions—not just advise on them—while staying deeply technical.
Our summary, not Hims and Hers’s wording. The full posting is on their site.
Skills this role names
- Apache Airflow
- Apache Flink
- Apache Kafka
- Databricks
- Dialectical Behavior Therapy (DBT)
- Go
- Google BigQuery
- Hightouch
- PySpark
- Python
- SQL
- Terraform
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What they ask for
Required
- 15+ years building and owning data platform architecture across multiple companies or platform generations
- Evidence of setting technical direction for organizations without direct management
- Experience defining boundaries of architectural authority
- Deep GCP and BigQuery expertise with operational fluency in AWS/EKS
- Modern data stack proficiency: dbt, Airflow/Astronomer, Kafka/Confluent, Databricks/Spark, Fivetran, and reverse ETL platforms
- Event streaming in production at scale including Schema Registry, data contracts, and consumer lag management
- Data governance and compliance in regulated healthcare environments: HIPAA, PHI handling, data classification, access controls, audit logging, GDPR
- Terraform or equivalent infrastructure-as-code
- Strong Python and SQL for production pipeline code review
- Written communication that creates alignment across organizations
Nice to have
- Databricks, Unity Catalog, and Delta Lake in production at scale
- CDC patterns and Flink for real-time processing serving analytics and production paths
- PySpark and SparkSQL for large-scale batch and streaming
- Led a BigQuery to Databricks Lakehouse or equivalent warehouse migration end-to-end
- MLOps partnership: model training pipelines, feature stores, experimentation infrastructure
- Go or Python service development for Kafka producers and consumers
- Direct-to-consumer healthcare or telehealth with HIPAA and GDPR obligations
- SOX compliance controls in data engineering context