Senior / Staff Data Platform Engineer

About Radar Radar https://radar.com is the global leader in geolocation, with geofencing SDKs, maps APIs, and AI-enabled solutions for marketing, fraud, and operations teams. Why is Radar the best place to work? - We're trusted by some of the world's best companies, from high-growth startups to the Fortune 500. - We have incredible scale: We're processing over 1 billion API calls per day from hundreds of millions of devices. - We're well-resourced, and we've raised $85.5M from world-class investors, including Accel and Insight Partners. - We have a high-performance culture, with ambitious and entrepreneurial teammates in every role. - We recently moved into an amazing new office in Flatiron, Manhattan, NYC. - We were recently named a top 10 best place to work in NYC by Crain's. Despite our growth and scale, we're still just getting started. That's where you come in. About the role We're looking for a Data Platform Engineer to build out the next generation of our data platform . The ideal candidate has been a data platform engineer on a large system and is energized by deeply understanding customer pain points and opportunities related to our data platform. To date this has been a shared responsibility on our engineering team, but as we've grown to over 1 billion API calls per day (with lots of data exhaust into our data lake), we're hiring a Data Platform Engineering team to modernize and level up our data stack. This role can be either in our NYC HQ or remote in the US. How we work: Most of our engineering team are former technical co-founders or former Radar interns from schools like Waterloo and CMU. Most engineers at Radar fit one of two molds, technically: either Staff level expertise in one stack, or "Multi-Stack" at any level. We say "Multi-Stack" because "Full-Stack" has the connotation of "Frontend and Backend", but Radar Engineers might also work on Mobile or Data engineering. Not that you need to be an expert in all of those, but a desire to learn, jump around to different stacks, and get things done is the important part. We care a lot about shipping fast and talking to customers. We're committed to our product vision of full-stack location infrastructure, but we also know that customer feedback is a treasure map to gold. Even though Slack is the brain of our company, working together in-person in our NYC HQ is the fastest way for us to get things done. We meet on Mondays to plan out work for the week in small groups and use Linear for planning. All projects are run by an Engineering lead, an executive and a Go-to-Market lead. Engineers figure out what to build, talk to customers, talk to prospects, help close them, get them live and make them successful. One of our most important company values is "Walk a mile," as in walking a mile in the customer's shoes, but also as in literally walking a mile, getting up from your desk and developing a deep understanding of how location services behave in the real world. To us, a week is a long time, and we expect to ship big things every week. The stack: - Our data stack includes Kinesis, S3, Athena, Terraform, Airflow, Parquet, Metabase, Python, Redis, MongoDB, and Kubernetes. - Our primary languages are TypeScript, Rust, and Python. - Most engineers are in the on-call rotation. - We sponsor OpenStreetMaps, MapLibre, and OpenAddresses. How we use AI: - Engineers choose what AI tools they use, Claude and Codex being the most popular. - We're actively building Claude skills - for example we've taught it how to debug HorizonDB, our geospatial database. - All code changes are reviewed by an Engineer knowledgeable in that area. Claude and Codex also review all PRs. - There is a range of how much engineers use AI. Most use it daily if not weekly. - We are excited about what AI can do, but we also recognize the risks and don't compromise our coding standards. The hiring process: After a call with our Technical Recruiter, you'll do several technical Zoom calls with members of our engineering team: code screen, coding round, and system design round. If those go well we'll invite you to our NYC HQ for a final round interview. You'll meet one of our co-founders, someone from outside engineering, and meet more people from Radar. We'll go into more depth about how we work to see if there is a match. What you’ll do: - Work on core Radar data infrastructure built with Kinesis, S3, Athena, Terraform, Airflow, Parquet, Metabase, Python, Redis, and Mongo (some of these need to be replaced - you'll help figure out what that looks like) - Improve our current data platform via incremental improvements and deploying next generation infra to level up our stack. - Talk to Radar customers and prospects, hear their feedback, incorporate it into your work and make them successful You should: - Have experience building data infrastructure - Besides experience with some of our current data stack, have experience with several of Snowflake, Clickhouse, Databricks, Dynamo and dbt or similar tools - Are interested in talking to customers or prospects and making them successful - Are deeply curious about how things work, and have the tenacity to sit with hard problems and power through them Bonus points if you: - Are a former technical co-founder - Have experience building end-to-end customer facing analytics, real-time streaming solutions, leveraging cold and hot storage to achieve product goals You’ll work with: - Tim Julien https://www.linkedin.com/in/timjulien/, CTO - Our customers and prospects - Our Customer Success, Sales Engineering, and Sales teams What we offer: - Competitive salary - Meaningful stock options in a fast-growing company - 401(k) plan with 4% match - New HQ in Flatiron, NYC - Top-notch equipment - Catered lunches - Unlimited PTO - Health, dental, and vision insurance with 100% coverage for employees - 12 weeks of paid parental leave - Commuter and fitness benefits We’ll share full details of our benefits package at the offer stage. Benefits may vary by location. Radar is an equal opportunity employer and does not discriminate on the basis of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, veteran status, or any other characteristic protected by law.