Principal Data Engineer

• We’re looking for a Principal Data Engineer to be the most senior individual contributor on the Data Platform Engineering (DPE) team at Hims & Hers
• In this role, you will define and align the architectural vision for our data platform with business goals – working in close partnership with product, engineering, and data science leadership
• Your scope is org-wide: you will set technical direction across every surface DPE owns, drive the highest-stakes architectural decisions, and establish the standards that the entire data engineering discipline operates by
• Our platform serves millions of patients across telehealth, prescription, and wellness products
• It runs on GCP BigQuery, Airflow on Astronomer/EKS, dbt, Confluent Kafka, Databricks Delta Lake, and Terraform/OpenTofu – and it is in active, consequential evolution: a net-new streaming platform, and a lower environments strategy being built from scratch
• You will own those architectural bets
• Own the long-term technical architecture for DPE across ingestion, orchestration, event streaming, and the platform infrastructure that enables transformation and serving - driving the highest-stakes decisions for the CDC-based streaming platform (Kafka → Flink → BigQuery), orchestration platform evaluation, and lower environment strategy
• Chair Architecture Review Committee (ARC) decisions; act as the primary technical DRI for cross-team, multi-system, and cost-impacting changes
• Establish and enforce engineering standards and production readiness criteria across all DPE-owned systems - testing requirements, CI/CD patterns, observability-as-code, logging standards, data contracts, Schema Registry governance, and what ‘production-ready’ means for emerging streaming and CDC capabilities
• Own data quality and observability architecture - dbt anomaly detection frameworks, schema validation, data drift alerting, and the platform standards that ensure consumers can trust the data they build on
• Define the technical strategy for self-service analytics: what platform capabilities enable Analytics Engineering to work independently, what guardrails prevent downstream breakage, and how DPE reduces its bottleneck over time
• Own evaluation, onboarding, and ongoing governance of DPE-managed tooling - Fivetran, Confluent, and equivalent platforms, including contract management, cost tracking, and deprecation decisions
• Own data sharing and egress patterns - access provisioning, cross-team data contracts, reverse ETL (Hightouch), and governed consumption paths for internal and external consumers
• Drive cost governance for platform infrastructure - BigQuery slot reservations, query optimization, partition strategies, orchestration rightsizing, and cloud spend accountability across the full DPE stack
• Lead incident response for platform-level P1/P2 incidents: act as technical escalation point, facilitate blameless RCAs, and drive systemic fixes that prevent recurrence
• Produce exemplary technical artifacts - architecture decision records, solution design docs, RFCs - that create alignment and become the team’s reference standard
• Mentor and elevate Staff and Senior Data Engineers; raise the technical ceiling through design reviews, code reviews, and hands-on pairing
• Partner cross-functionally with ML/Data Science, legal/security/compliance, and DevOps to deliver platform capabilities that are ML-ready, compliant with HIPAA/GDPR, and hardened at the infrastructure layer
• Contribute hands-on to critical path work

Benefits

• Generous PTO: Take the time you need, when you need it - including generous parental leave
• Full healthcare: High-coverage medical, dental & vision coverage for individuals and families
• Retirement planning: Take advantage of our 401(k) plan including contribution matching
• Work from anywhere: We are a remote-first company, so you can work from anywhere you like in the uS
• Robust compensation: We offer competitive salary bands and stock options
• Employee discount: Employees can take advantage of product discounts
• Utility stipend: A extra $75 each month to cover extra cell phone, internet, or data usage
• Spending accounts: Options for additional HSA and FSA plans to help toward healthcare costs

• Experience owning data quality frameworks - dbt testing, anomaly detection, schema validation, and data observability tooling
• Clear written communication: you produce design docs and RFCs that build alignment, not confusion. Comfort operating in ambiguity - you define the path, you don’t wait for it to be defined
• Hands-on experience with the modern data stack: experience governing dbt at platform scale, Airflow/Astronomer, Kafka/Confluent, Databricks/Spark, Fivetran, and data sharing/activation platforms (Hightouch or equivalent)
• Demonstrated ability to define and align architectural vision with business goals across an entire engineering organization
• 15+ years of professional experience designing, building, and owning data platform architecture at company scale
• Experience designing and operating event streaming pipelines at scale - including Schema Registry, data contracts, and consumer lag management
• Infrastructure-as-code fluency - Terraform or equivalent; you treat infrastructure changes like software changes
• Deep expertise in cloud-native data platforms across GCP primary (BigQuery, GCS, Dataflow); AWS operational familiarity required (EKS-based Airflow) - BigQuery strongly preferred; multi-cloud fluency is required, not a plus
• Experience with data governance and compliance frameworks in a regulated environment - HIPAA/PHI handling, data classification, access controls, audit logging, and GDPR
• Experience leading incident response for data platform outages - blameless RCA, systemic root cause identification, and operational improvement
• Proven track record establishing engineering standards across multiple teams and driving adoption without direct authority
• Strong Python and SQL skills; comfortable writing, reviewing, and raising the bar on production-grade pipeline code
• 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
• PySpark/SparkSQL for large-scale batch and streaming workloads
• Experience with MLOps - partnering with ML engineers on model training pipelines, feature stores, and experimentation infrastructure
• Databricks, Unity Catalog, and Delta Lake in production at scale
• Go or Python service development for Kafka producers and consumers
• Experience driving a BigQuery → Databricks Lakehouse migration or equivalent cloud data warehouse migration
• Familiarity with SOX compliance controls in a data engineering context
• Experience at a direct-to-consumer healthcare or telehealth company with HIPAA and GDPR obligations
• Experience with CDC (Change Data Capture) patterns and Flink for real-time data processing