Staff Data Engineer

Radar•Sunnyvale, CA

About The Position

RADAR is seeking a Staff Data Engineer to contribute to the development of its analytics, Machine Learning, and AI capabilities. This role involves close collaboration with various departments, including product, customer success, engineering, data science, and research. The Staff Data Engineer will be instrumental in designing, building, and maintaining scalable data pipelines, optimizing data models, and contributing to the company's data product offering. This position also entails owning the technical direction of the data platform and mentoring other data engineers.

Requirements

8+ years in an Analytics Engineering or Data Engineering role, including experience setting technical direction and mentoring other engineers.
Strong proficiency with large-scale query tools such as SQL or Apache Spark, and comfort with Python for data manipulation and building orchestration and streaming pipelines.
Experience developing, maintaining, and monitoring large data pipelines with an orchestration tool (Airflow, Dagster, or dbt) for batch and a streaming framework (Apache Beam, Kafka Streams, Flink, or similar).
Solid grasp of large-scale data fundamentals — partitioning strategies, SQL query performance optimization, cost/performance tradeoffs.
Experience developing data models that support scalable, cost-effective analytics and ML pipelines.
Experience writing data quality checks and unit and integration tests to ensure high-quality data and analytics.
Experience creating analytics solutions with visualization tools such as Looker or Tableau.
Proficiency with version control (Git).

Nice To Haves

Experience building pipelines that support ML model training and serving.
Experience with modern data warehouses such as Snowflake, Databricks, or BigQuery.
Experience with containerization tools such as Docker.
Bachelor's or Master's degree in a relevant field, or equivalent practical experience.

Responsibilities

Design, build, and maintain scalable, reliable data pipelines (batch and streaming) with Airflow, Beam, and Python — including the data quality checks, testing, monitoring, and error handling that keep them trustworthy.
Design data models that make analytics and ML pipelines scalable, repeatable, and cost-efficient.
Write and optimize complex SQL (CTEs, window functions) and streaming pipelines in Python.
Partner with data science, engineering, and product to turn data needs into solutions.
Build RADAR's data product offering — turning our real time inventory and location data into actionable insights for our retail partners — and the visualizations and dashboards (e.g. Looker) that turn data into decisions.
Own the technical direction of the data platform — architecture, technology, standards, and roadmap.
Mentor data engineers and set the standards the team builds on for scalable and reliable data pipelines.