Staff Data Engineer

Responsibilities

• Lead platform modernization efforts across the analytics ecosystem, including deprecating legacy workflows, migrating pipelines to scalable patterns, and improving infrastructure, CI/CD, and developer experience.
• Drive high-leverage infrastructure and FinOps initiatives across systems like Snowflake, Dagster, and dbt to reduce cost, improve governance, and increase scalability.
• Own platform evolution projects such as making data more consumable by agentic tools and improving orchestration tooling.
• Design and deliver complex, domain-critical data products used by analysts, data scientists, and product teams.
• Architect scalable patterns for modeling, orchestration, and data transformation.
• Lead technical planning and delivery across cross-functional teams.
• Drive platform adoption and best practices, mentoring engineers and building documentation.
• Partner with engineering, product, data science, and business stakeholders.
• Represent Data Engineering in technical design forums and roadmap discussions.

Requirements

• 8+ years of experience in data or analytics engineering with a track record of owning complex, business-critical data systems end to end.
• Deep experience with the modern data stack (Snowflake, dbt, Dagster, Databricks), Terraform, and cloud infrastructure.
• Track record of leading platform migrations, deprecations, or upgrades.
• Experience designing secure, reusable patterns for data ingestion, access control, and platform automation.
• Experience with DevOps practices (CI/CD for data), data governance, or FinOps.
• Ability to break down ambiguous, cross-functional data problems and lead implementation from design to deployment.
• Strong communication skills across technical and non-technical audiences.
• Excitement about mentoring others and improving systems.

Nice-to-Haves

• Experience supporting machine learning workflows.
• Experience in a fast-growing startup environment or on platform-style teams.