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Analytics Engineer

Monzo LogoMonzo
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Our Analytics Engineering discipline works in the intersection between data, engineering and our collectives - Money, Borrowing, Operations and Financial Crime and beyond. The team is responsible for building downstream data models from backend services with the desire to make our Data Warehouse a genuine competitive advantage for Monzo. We want a discipline capable of building an amazing Data Warehouse to support decision making, Business Intelligence, key financial reconciliation processes and best in class analytics and Data Science.

You'll be an individual contributor in our Analytics Engineering team, working across a variety of projects to spot patterns in the way we build our Data Warehouse and optimise our BI platform, Looker. You’ll help us load and transform even more data, minimise our cloud costs, contribute using our best practices, keeping quality high.

We are at an exciting stage in our growth and have roles available across Wealth, Business Banking and Fincrime, so do let us know if you’re interested in a specific area.

What you’ll be working on:

Your day-to-day

Working in a multi-disciplinary data / engineering squad, you will:

  • Support the building of robust pipelines and data models downstream of backend services (mostly in BigQuery) that support internal reporting, machine learning as well as financial and regulatory use cases.
  • Build with optimisation of our Data Warehouse in mind, spotting and raising opportunities to reduce complexity and cost.
  • Help define and manage best practices for our Data Warehouse. This may include payload design of source data, logical data modelling, implementation, metadata and testing standards.
  • Follow our established best practices and standards defined by the team
  • Investigate and effectively work with colleagues from other disciplines to monitor and improve data quality within the warehouse.

You should apply if:

  • You have some experience and a passion for Data Modelling, ETL projects and Big Data as an engineer, developer or analyst.
  • You are confident with SQL and data modelling
  • You are an comfortable with general Data Warehousing concepts
  • You have an eye for detail
  • You’re ready to be part of a growing team in new areas of growth!

The interview process:

Our interview process involves 3 main stages:

  • Initial Call
  • Take home task
  • Final Stage

Our average process takes around 2-3 weeks but we will always work around your availability.

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