Principal Data Engineer

hims & hers

Principal Data Engineer defining and aligning architectural vision for healthcare platform data with business goals. Leading high-level decisions and ensuring data quality and observability across teams.

Posted 7/28/2026full-timeRemote • 🇺🇸 United StatesLead💰 $220,000 - $260,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in designing and owning cloud-native data platform architecture, with a strong focus on data quality, observability, and compliance frameworks. Proven ability to lead cross-functional teams and establish engineering standards that align with business goals.

Highest-signal resume keywords

Cloud-Native Data PlatformsData Quality FrameworksEvent Streaming PipelinesInfrastructure-As-CodeData Governance Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

BigQueryGCPSQLPythonTerraformKafkaDbtAirflowData GovernanceSchema Registry

Soft Skills

Clear Written CommunicationMentoringCross-Functional CollaborationIncident Response Leadership

Tools & Technologies

FivetranHightouchConfluentDatabricksDataflow

Industry Keywords

HIPAAGDPRData ContractsAnomaly DetectionOperational Improvement

Tech Stack

Tools & technologies

AirflowAWSBigQueryCloudETLGoogle Cloud PlatformKafkaPythonSparkSQLTerraform

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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.

Benefits

Comp & perks

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