Data Engineer at Button
New York City, NY, US
Button’s mission is to be "the better way" in mobile commerce. Today, we work with some of the largest and most interesting businesses in the world to connect consumers with what they want at the tap of a button. We build with the consumer experience in mind, and we have a reputation for paving the future of mobile and enjoying the road to get there. Data will be the foundation for building our next generation of products—and that's where you come in.
As a Data Engineer, you will help build the systems responsible for ingesting, processing, and analyzing the data streams that drive key decisions we and our customers make. You will work on integrating machine learning and ETL systems that process billions of events, built on Redshift, SQS, and Airflow, and written in Python and Go. You will be a close partner to Button’s Data Science team to craft and refine the reusable components of our data platform


    • Work with data scientists and data analysts to design, build, and deploy reusable components for data storage, data processing, machine learning, and data accessibility.
    • Expand our pipeline instrumentation and tooling with monitoring, alerting, logging and tracing for our critical business tasks.
    • Support new feature development as the data partner. You’ll be involved end-to-end, helping lean, cross-disciplinary product engineering teams define and execute on the product’s goals including measurement and embedding ML frameworks.


    • Experience with and a desire to continue learning about data infrastructure and frameworks. Right now, we make heavy use of ECS, Redshift, Airflow, and BigQuery — but we are eager to learn more.
    • Strong fundamentals including SQL, databases and ETL best practices.
    • Programming experience in Python or Go. Experience writing production code that others can understand. Bonus points for experience with the Python scientific stack.
    • An awareness of the landscape of available data storage and processing tools.


    • Brad GroffDirector of Data: Brad is the head of the Data team at Button. Before joining us, he ran data science and data engineering at Ordergroove, and managed data science teams at Capital One and Booz Allen Hamilton. In his free time, he can be found engaging in lengthy discussions with his daughter on topics such as which colors are his favorite colors and why, how some monsters can be nice and others can be mean (but sometimes just because they're hungry), and which things are the silliest things
    • James (or Jimmy) McGillVP of Engineering: Hailing formerly from both Australia and Google, he spends his weekends hiking, surfing and designing and building furniture. See James for all of your Vegemite needs.
    •  Wilson TsaoAnalytics Manager: is a member of the Data Science team at Button. Previously he was in similar roles at Eventbrite, Yingli Solar, and Goldman Sachs. He enjoys playing and watching basketball in his spare time.
    • Mijail GomezData Science Engineer: has worked on event ingestion, data processing frameworks, data standardization, and experimentation frameworks. He loves having discussions on data architecture, systems and tech. Before Button he was in SF working in early stage startups. Outside of work he enjoys soccer, hiking, and exploring new burger places in NYC.
Button is committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported and connected at work—regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives.
Button is an Equal Opportunity Employer. We do not discriminate against qualified applicants or employees on the basis of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by federal, state, or local law, rule, or regulation.

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