ABOUT THE JOB

We are looking for a Staff Data Engineer to help build and develop our analytics, Machine Learning and AI capabilities at RADAR. The role requires extensive collaboration with teams and functions across the company ranging from product and customer success to engineering, data science and research.

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.

ABOUT YOU

Required:

• 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).

Preferred:

• 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.

WHAT YOU'LL DO

In your first 30 days, you will:

• Complete onboarding, security, and compliance training, and get to know RADAR's mission, stack, and values.
• Meet key stakeholders across the org and start building relationships beyond your immediate team.
• Develop a working understanding of RADAR's data architecture — BigQuery tables, batch and streaming pipelines.
• Ship a meaningful contribution to an active pipeline, getting hands-on with the codebase and tooling.
• Begin forming a point of view on where the data platform can improve.

In your first 60 days, you will:

• Take ownership of a meaningful component of the data platform — a pipeline, data model, or domain — and be the go-to person for it.
• Deliver improvements to reliability, cost, or performance on an existing pipeline, applying data quality checks, testing, and monitoring as you go.
• Partner directly with data science, engineering, or product on an active need, translating an ambiguous requirement into a shipped solution.
• Turn your early observations into a concrete, prioritized list of where the data architecture and technology stack can improve — and socialize it with the team.

In your first 90 days, you will:

• Own and drive a piece of the data platform roadmap, from proposal through delivery, making the architecture and build-vs-buy tradeoffs it requires.
• Establish or level up a team standard for data modeling, and get the team aligned behind it.
• Mentor other engineers through code reviews, design discussions, and pairing — raising the bar on how the team builds.
• Deliver measurable impact on RADAR's data product offering, helping turn real-time inventory and location data into insights partners can act on.

At RADAR, your base pay is one part of your total compensation package. The expected base salary range for this position is $200,000-$260,000. Individual pay is determined by work location and additional factors,  including job-related skills, experience and relevant education or training.You will also be eligible to receive other benefits including: equity, comprehensive medical and dental coverage, life and disability benefits, 401k plan,  flexible time off, and paid parental leave. The pay range listed for this position is a good faith and reasonable estimate of the range of possible base compensation at the time of posting. 

Research has shown that women & underrepresented minorities are more likely to read lists of requirements and consider themselves unqualified if they don't meet every single one. This list represents what we're ideally looking for, but everyone has unique strengths & weaknesses, and we hire for strength & potential, not lack of weakness.