Set the technical vision for the data platform: Own the long-term architectural direction for how streaming and batch systems, data models, and serving layers fit together. Make the architectural decisions that other teams and engineers build on — balancing reliability, performance, cost, and long-term maintainability across the platform.
Build at the intersection of data and ML platform: Design the infrastructure that connects the data platform to ML workloads — feature pipelines, feature stores, and serving layers.
Raise the engineering bar across the organization: Set standards that extend beyond your immediate team — data modeling patterns, schema governance, testing practices, pipeline reliability, and code quality.
Drive cross-organizational technical initiatives: Lead complex initiatives that span multiple teams, services, and domains.
Own platform reliability and operational excellence: Drive the reliability posture of the most critical data systems.

Bachelor’s Degree (or equivalent) in Computer Science, Engineering, or a related technical field.
10+ years of hands-on data engineering experience, with a significant portion spent in platform or infrastructure roles building systems that other teams depend on.
Experience architecting data systems across batch and streaming paradigms, including technologies such as Kafka, Flink, Spark, or equivalent.
Strong proficiency in Python and SQL, with deep experience in distributed data processing frameworks and data platform design.
Data and ML platform crossover: You've built or contributed to ML platform infrastructure — feature pipelines, feature stores, model serving, or MLOps tooling — as a natural extension of your data engineering work.
Track record of setting technical direction across an organization — driving alignment across multiple teams, making architectural decisions with broad impact, and delivering outcomes without formal authority.
Demonstrated experience mentoring senior engineers and influencing engineering culture and standards beyond your immediate team.

Inclusive healthcare and benefits: On top of comprehensive medical, dental, and vision coverage, we offer employees and their family members help with gender-affirming care, tools for family and fertility planning, and travel reimbursements if healthcare isn’t available where you live.
Planning for the future: Start saving for the future with our traditional or Roth 401k retirement plan options which include a 2% company match.
Modern life stipends: Manage your own learning and development
Grow with us through discounted company stock through our ESPP with easy payroll deductions.

Senior Staff Data Engineer – Data & ML Platform

Key skills