Data Engineer (Senior)

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Locations: London

Mind Gym uses the latest behavioral science to transform the performance of companies and the lives of people who work in them. Most of FTSE100/S&P100 are clients and over 2 million professionals in 60 countries have taken part in a live Mind Gym experience, whilst many more have connected digitally.

We’re growing rapidly and have successfully floated on the London Stock Exchange.  This is just the start.  We have a bold vision to redefine how companies and individuals flourish, and so disrupt the market for behavioural change.

If you’re determined to make a difference, voraciously curious and brimming with entrepreneurial spirit, we’d like to hear from you.

The Job:

The technology team in Mind Gym is newly created. We are working on a greenfield technology platform build that will transform the business.

As a data engineer (senior), you will be responsible for shaping and implementing our data strategy with a variety of streams piping to an AWS based data lake and warehouse. We expect our stack to include RedShift, Parquet on S3, Python based ETL and possibly Snowplow. For infrastructure we use AWS and Kubernetes alongside a modern DevOps stack.

A typical day might include:


  • Working as part of a cross functional “mission team” to design, document and implement new features.
  • Getting involved with normal agile ceremonies that prepare, co-ordinate and reflect on the team’s throughput.
  • Running, operating and caring for the platform that we build.
  • Tracking and improving software delivery performance with the “four key metrics”.
  • Following great data engineering practices with clean code / modelling, managing data quality, TDD and only building what you need.
  • Helping us build a generative team culture with high co-operation, shared risks, encouraged bridging and blame free post-mortems.


About you:


  • Significant experience of being a data engineer
  • Experience with Python and Pandas in a containerised environment
  • Experience of data modelling techniques and query languages
  • Experience of different data storage / retrieval, encoding and evolution techniques
  • Experience of working in a distributed and high-volume environment
  • Experience of Amazon Redshift and the surrounding ecosystem
  • Critical thinking on when to build vs buy
  • Cloud native in AWS or GCP


  • You know how which levers accelerate delivery with the “4 key metrics”
  • Good experience of dealing with competing stakeholder needs
  • Laying the early groundwork for data science teams
  • Your stack extends to Kubernetes and Docker

If this sounds like something you’d be great at, we’d love to hear from you.

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