Senior Analytics Engineer
Monzo (View all Jobs)
Cardiff, London or Remote (UK)
1. Phone interview 2. Take-home, & call to discuss it 3. 2-3 hours of on-site interviews (systems/behavioural)
Programming Languages Mentioned
SQL, Python, ETL
📍London / UK Remote
We’re here to make money work for everyone and we're doing things differently. For too long, banking has been obtuse, complex and opaque.
We want to change that and build a bank with everyone, for everyone. Our amazing community suggests features, test the app and give us constant feedback so we can build something everyone loves.
We're focused on solving problems, rather than selling financial products. We want to make the world a better place and change people's lives through Monzo.
About our Team:
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 a senior 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 minimise our cloud costs, drive best practices across all of our Data Discipline and scale and automate our data governance.
Enable Monzo to Make Better Decisions, Faster
At the core of this mission sits our data platform. We're great believers in powerful, real-time analytics and empowerment of the wider business. Every engineer at Monzo is responsible for collection of relevant analytics events from their microservices. We optimise for simplicity and re-usability – all our data lives in one place and is made available via our data warehouse in Google BigQuery. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.
What you’ll be working on:
Working in a multi-disciplinary data / engineering squad, you will:
- 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
You should Apply if
- You have experience and a passion for Data Modelling, ETL projects and Big Data as a developer or analyst.
- SQL and data modelling are second nature to you
- You are an comfortable with general Data Warehousing concepts
- You strive for improvement in your work and that of others, proactively identifying issues and opportunities
- You have experience building robust and reliable data sets requiring a high level of control
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)
The Interview Process:
Our interview process involves 3 main stages:
- First stage
- Take home task
- Final stage
Our average process takes around 2-3 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 email@example.com
What’s in it for you:
✈️ We can help you relocate to the UK
✅ We can sponsor visas
📍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.
Equal Opportunity Statement
We are actively creating an equitable environment for every Monzonaut to thrive.
Diversity and inclusion are a priority for us and we are making sure we have lots of support for all of our people to grow at Monzo. At Monzo, embracing diversity in all of its forms and fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2021 Diversity and Inclusion Report and 2022 Gender Pay Gap Report.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.
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