hims-and-hers - Principal Data Engineer
Requirements
• 15+ years of professional experience designing, building, and owning data platform architecture at company scale • Demonstrated ability to define and align architectural vision with business goals across an entire engineering organization • 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 • 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) • Experience designing and operating event streaming pipelines at scale - including Schema Registry, data contracts, and consumer lag management • Proven track record establishing engineering standards across multiple teams and driving adoption without direct authority • Experience owning data quality frameworks - dbt testing, anomaly detection, schema validation, and data observability tooling • 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 • Infrastructure-as-code fluency - Terraform or equivalent; you treat infrastructure changes like software changes • Strong Python and SQL skills; comfortable writing, reviewing, and raising the bar on production-grade pipeline code • 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 • Databricks, Unity Catalog, and Delta Lake in production at scale • Experience with CDC (Change Data Capture) patterns and Flink for real-time data processing • PySpark/SparkSQL for large-scale batch and streaming workloads • Experience driving a BigQuery → Databricks Lakehouse migration or equivalent cloud data warehouse migration • Experience with MLOps - partnering with ML engineers on model training pipelines, feature stores, and experimentation infrastructure • Go or Python service development for Kafka producers and consumers • Experience at a direct-to-consumer healthcare or telehealth company with HIPAA and GDPR obligations • Familiarity with SOX compliance controls in a data engineering context • OUR BENEFITS (THERE ARE MORE BUT HERE ARE SOME HIGHLIGHTS): • Competitive salary & equity compensation for full-time roles • Unlimited PTO, company holidays, and quarterly mental health days • Comprehensive health benefits including medical, dental & vision, and parental leave • Employee Stock Purchase Program (ESPP) • 401k benefits with employer matching contribution • Offsite team retreats • Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws. • It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. • Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at [email protected] and describe the needed accommodation. Your privacy is important to us, and any information you share will only be used for the legitimate purpose of considering your request for accommodation. Hims & Hers gives consideration to all qualified applicants without regard to any protected status, including disability. Please do not send resumes to this email address. • To learn more about how we collect, use, retain, and disclose Personal Information, please visit our Global Candidate Privacy Statement https://www.hims.com/global-candidate-privacy-statement.
Responsibilities
• 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
• $220K – $260K • Offers Equity • The actual amount will take into account a range of factors that are considered in making compensation decisions, including but not limited to skill sets, experience and training, licensure and certifications, and location. H&H also offers a comprehensive Total Rewards package that may include an equity grant. • Consult with your Recruiter during any potential screening to determine a more targeted range based on location and job-related factors. • This job has application limits • To ensure that we can give proper consideration to everyone who's excited about joining Hims & Hers, we ask that you please only apply to a specific role once within a 60-day period. If you weren’t selected this time, you are welcome to check back and reapply after 60 days. • We truly appreciate your interest in Hims & Hers and look forward to staying connected! • Autofill from resume • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • Candidate Information • or drag and drop here • LinkedIn Profile URL • If you don't have a LinkedIn profile, please write NA • How many years have you spent designing, building, and owning data platform architecture? • Of those years, how much was owning architecture company wide versus just for your own team? • Mostly company wide • Roughly half and half • Mostly team or squad level • All team or squad level • Which describes your Kafka or Confluent experience best? • I've set the architecture and standards other teams build on • I've designed and built streaming pipelines but didn't set standards beyond my team • I've implemented pipelines someone else designed
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