Data engineer

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Aampe is hiring a data engineer.

About us:

Our mission is to help mobile apps treat their users like people instead of like users. We repurpose push notifications to learn user preferences and then to give the people what they want, when they want it. We wrote a storybook to explain how we make the magic happen. We have to orchestrate a lot of moving, changing parts (data ingestion and processing, ML models, message triggering, user experience, etc.).

Log in to our Composer tool (sign up using a Google account or shoot an email to for an invite code) to get a glimpse of what this looks like.

We are a fully-remote startup, managing personalized notifications for over 45 million app users (and that number is quickly growing). We don’t think you should have to sacrifice yourself or your family to work for a startup: the salaries we pay are market rates, offer generous benefits, and expect 40 hours of dedicated, strong, focused work each week. As a team and a culture, we do everything we can to make sure our lives and our work energize one another rather than compete with one another.

About the position:

In general, we value efficiency and attention to detail (who doesn’t?), but we really value frankness and proactivity. We’re looking for people who quickly develop strong opinions, and who back up those opinions with both words and actions, but who also easily re-evaluate when faced with new needs or new information. 

Specifically for the data engineer position, we need people to design, implement, and operate complex data processing pipelines. This means you’ll analyze raw data, build data systems, work with data scientists to move ML algorithms into production, and help customers pipeline their data into our systems. We’re looking for someone who can confidently own this role - you’ll create most of the tasks you take on, rather than having them assigned to you.

You will be working on the Aampe data model design, the reliable ingestion of customer event data, the pipelines that generate features for Aampe’s learning models and making aggregate data available in our tool for customers.

About you (we hope!):

We’ll expect you to have pretty extensive experience with data processing methodologies and frameworks, especially as it concerns the processing of large amounts of data. We’ll expect you to write code that is clean and maintainable (we work primarily in Python and use SQL a whole lot). If you have experience with Apache Beam and/or Apache Airflow, we’d be excited about that. If we had to say how much experience we expect a successful candidate for this position to have, we’d guesstimate around five years, but if you have less than that but can make the case for why you’re a good fit, we’re happy to listen.

We’ll expect you to enjoy working closely (albeit usually virtually) with others - particularly with data scientists and backend engineers - and to have learning at the top of your priority list. Our company, our product, and our team are all evolving quickly - so all of us need to be flexible in our work but also in our thinking, so we can adapt as our opportunities change.

About applying:

If you’re interested, write to us at to tell us why you’re interested. Any questions about the role can be directed to Sami Abboud at Sami’s a nice guy. You’ll like him.

A summary of the above in bullets

Mission for a data engineer

Design, implement & operate complex data processing pipelines

What should you expect to do?

  • Analyze raw data
  • Build data systems & pipelines
  • Work hand in had with data scientists on taking ML algorithms to production
  • Help customers pipeline their data into Aampe


  • Extensive experience with data processing methodologies and frameworks
  • Extensive experience with dealing with large amounts of data
  • Strong experience with Python
  • Mastery of SQL
  • Bonus if you have experience developing for Apache Beam
  • Bonus if you worked with Apache Airflow before

This role fits data engineers who:

  • Write clean code and want to help build coding standards
  • Care about building a robust system that customers can rely on
  • Enjoy working closely with data scientists and backend engineers
  • Have learning at the top of their priority list
  • Come with strong opinions that they can easily re-evaluate when faced with new evidence
  • Enjoy a fully-remote setting