Senior Analytics Engineer
Monzoreferrals · Germany
Skills in this posting
Benefits
The posting
📍 London, Cardiff or Remote in the UK | Benefits | Hear from the team ✨| Check out our Career Launchpad 🚀
What you’ll be working on
The Analytics Engineering 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 enable our data driven approach, and
Support the building of robust data models downstream of backend services (mostly in BigQuery) that support internal reporting, machine learning as well as financial and regulatory use cases.
Focus on optimisation of our Data Warehouse, spotting 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.
Set standards and ways of working with data across Monzo, working collaboratively with others to make it happen.
Take established best practices and standards defined by the team, applying them within other areas of the business.
Investigate and effectively work with colleagues from other disciplines to monitor and improve data quality within the warehouse.
Contribute to prioritisation of data governance issues
We all own and support the pipelines we contribute to, and on call support out of hours will be expected from time to time as part of this role
We’d love to hear from you if…
You enjoy working with cross functional fast moving teams and are passionate about serving small businesses.
You are able to think strategically about the Business Banking product and how our underlying data models will unlock more insights for our team and more value for our customers.
You have a strong passion for data modelling, ETL projects, and Big Data.
You enjoy working with data streams from various services, such as financial, transactional, and operational systems.
SQL and data modelling are second nature to you, and you are comfortable with general Data Warehousing concepts.
You are committed to continuous improvement, proactively identifying opportunities and addressing challenges in your work and the work of others.
Nice to haves
Any experience working within a finance function or knowledge of accounting.
Experience working in a highly regulated environment (e.g. finance, gaming, food, health care).
Knowledge of regulatory reporting and treasury operations in retail banking
Exposure to Python, Go or similar languages.
Experience working with orchestration frameworks such as Airflow/Luigi
Have previously used dbt, dataform or similar tooling.
Used to AGILE ways of working (Kanban, Scrum)
Our interview process involves 3 main stages
30 minute recruiter call
45 minute call with the hiring manager
Take home task
2-part final stage
Our average process takes around 3 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on ----- Please also use that email to let us know if there's anything we can do to make your application process easier for you, because of disability, neurodiversity or any other personal reason.
What’s in it for you
📍This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London).
⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
📚Learning budget of £1,000 a year for books, training courses and conferences
➕And much more, see our full list of benefits here
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
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