Lead Data Platform Architect

Socket.dev; United States; Remote; USD 180,000 - 280,000; Full time

Benefits offered by this job

Competitive salary & equity

Unlimited PTO

Comprehensive health benefits

Employee Stock Purchase Program

401k with employer matching

Offsite team retreats

Job summary

Hims & Hers is seeking a Principal Data Engineer to lead the Data Platform Engineering team. You will define the architectural vision for the data platform, collaborating with product, engineering and data science leadership to set standards and drive strategic initiatives at scale.

You will own streaming, ingestion, orchestration, and platform infrastructure decisions, ensure data quality and governance, and mentor staff engineers while partnering with ML/DS and security/compliance to

Qualifications

• 15+ years designing data platform architecture at scale.
• Ability to align architectural vision with business goals across an engineering org.
• Strong Python and SQL skills and production-grade pipeline experience.
• Hands-on data governance, data quality, and observability tooling experience.

Responsibilities

• Define and align architectural vision for the data platform across ingestion, orchestration, event streaming, and infrastructure.
• Chair Architecture Review Committee and drive cross-team technical decisions with cost impact.
• Establish engineering standards and production readiness criteria across DPE systems.
• Own data quality and observability frameworks including dbt testing and schema validation.
• Lead incident response for data platform outages and drive systemic fixes.

Skills

Python

SQL

Tools

BigQuery

Airflow

dbt

Confluent Kafka

Databricks

Terraform

Job description

Hims & Hers is seeking a Principal Data Engineer to lead the Data Platform Engineering team. You will define the architectural vision for the data platform, collaborating with product, engineering and data science leadership to set standards and drive strategic initiatives at scale.

You will own streaming, ingestion, orchestration, and platform infrastructure decisions, ensure data quality and governance, and mentor staff engineers while partnering with ML/DS and security/compliance to