Staff Data Engineer

Role overview Join a multidisciplinary engineering organization to shape the data platform behind a large-scale consumer health application. As a Staff Data Engineer, you will set technical direction for high-throughput, event-driven pipelines and partner closely with product, infrastructure, and analytics teams to deliver reliable data at scale.

Responsibilities - Design, build, and maintain high-throughput, event-driven data services and orchestration pipelines supporting analytics and product insights. - Architect and evolve core platform components, modernizing ingestion patterns such as CDC and event streaming to replace legacy pipelines. - Champion DataOps practices including data modeling, CI/CD, unit testing, and validation frameworks to ensure consistency across the data platform. - Define and evangelize data engineering standards, reviewing peers' work and providing implementation guidance across the broader organization. - Advance agentic development practices, expanding the share of recurring work handled by automated agents while embedding guardrails and safe AI usage. - Shape data governance strategy, including how internal tools and AI assistants safely access and query organizational data. - Own cost efficiency and stewardship for warehouse and pipeline infrastructure, balancing performance, reliability, and spend. - Mentor data engineers, foster technical growth, and lead cross-functional initiatives spanning infrastructure, data services, and observability.

Requirements - 8-12+ years in engineering roles, including 3-5+ years in data engineering at senior, architect, or staff level building end-to-end data platforms. - Extensive hands-on experience with a modern cloud data warehouse such as Snowflake or comparable technology. - Experience across distributed and non-distributed structured and unstructured stores, including relational databases, document stores, key-value stores, and object storage. - Advanced SQL skills, including authoring and optimizing complex queries against large-scale, high-cardinality datasets. - Strong experience with orchestration tools such as Airflow and writing high-throughput services in Python. - Proven experience with high-volume, event-driven architectures and modernizing legacy ingestion pipelines.

Nice to have - Modular modeling with dbt and semantic layer best practices. - Dataset versioning and CI enforcement. - Scaling and resilience techniques for data pipelines in high-velocity experimentation environments. - Data cataloging and governance tools such as Secoda or Snowflake Horizon and metadata stewardship programs. - Building or evaluating AI-assisted internal tools with deterministic, code-level business-rule enforcement. - Multi-agent orchestration or coordination patterns.

Benefits and work setup - Estimated salary range of $170,000 - $230,000, with actual compensation based on experience and other factors. - Mentorship program with matched teammates for career growth. - Paid maternity and paternity leave plus comprehensive fertility-related assistance. - Monthly wellness allowance and dedicated mental health days. - Peer recognition and reward platform. - Premium subscription access to the company's consumer health application. - Virtual learning and development library with ongoing training opportunities. - Active DEI committee driving inclusive workplace practices. - Competitive medical, dental, and vision benefits. - Retirement savings program with employer match. - Equal opportunity employer with E-Verify participation.