We are seeking a highly experienced and forward-thinking Staff Data Engineer to lead the design and evolution of our data infrastructure. In this senior-level position, you’ll architect scalable, high-performance systems that enable analyzing site traffic, telemetry, search performance, and advertising effectiveness. You will also collaborate closely with software engineers and data scientists to build production-grade analytic data products and mentor other data engineers.

 

What You’ll Do

Design and implement end-to-end data architecture for real-time and streaming pipelines to support analytics and data products. Capture and process website telemetry data using tools like Segment and integrate with downstream systems for analysis. Optimize compute performance and cost in Snowflake, including query tuning, resource scaling, and data modeling best practices for analytic and reporting data. Leverage technologies like ClickHouse for fast, efficient storage and querying of large-scale log and event data for data products. Build and manage orchestration workflows with Airflow and manage real-time data pipelines using Estuary, including change data capture and event streaming. Design data models to support search algorithm performance analysis and analytics around advertising server outputs. Work directly with software engineers and stakeholders to define data product requirements and deliver impactful solutions. Mentor junior and mid-level data engineers, fostering best practices in code quality, testing, and architecture.

 

Requirements

10+ years of experience in data engineering and architecture, with a focus on real-time systems and scalable infrastructure. Hands-on experience with streaming data technologies (e.g., Kinesis) and real-time data integration platforms like Estuary. Proficient with Airflow for scheduling and orchestrating complex workflows. Knowledge of Snowflake and ClickHouse (or similar technologies) for database design and query optimization. Familiarity with customer data platforms for telemetry data capture (Segment preferred). Knowledge of GraphQL APIs in modern microservices environments. Solid understanding of AWS services including S3, Lambda, EC2, IAM, and data-related services. Strong skills in SQL, Python and dbt; experience with Spark or Scala, a plus.

 

Preferred Qualifications

Experience in ecommerce, ad tech, or content discovery/search platforms. Familiarity with data governance, observability, and lineage tools. Exposure to ML infrastructure or data science collaboration is a plus.

 

#LI-Hybrid