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- Tasks: Build and optimise data models for our Data Warehouse to support decision making.
- Company: Join Monzo, a leading fintech company revolutionising banking with data-driven insights.
- Benefits: Enjoy flexible working hours, a £1,000 learning budget, and remote work options.
- Why this job: Be part of a dynamic team that values innovation and collaboration in a fast-paced environment.
- Qualifications: Strong SQL skills, experience in data modelling, and a passion for Big Data are essential.
- Other info: Open to part-time work and supportive of diverse needs during the application process.
The predicted salary is between 43200 - 72000 £ per year.
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)
The Interview Process:
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 tech-hiring@monzo.com 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. #J-18808-Ljbffr
Senior Analytics Engineer employer: Referrals Only
Contact Detail:
Referrals Only Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as BigQuery, SQL, and data modelling. Having hands-on experience or projects showcasing your skills with these tools can set you apart during the interview process.
✨Tip Number 2
Prepare to discuss your experience with cross-functional teams and how you've contributed to data-driven decision-making in previous roles. Highlighting your collaborative skills will resonate well with the team-oriented culture at StudySmarter.
✨Tip Number 3
Research common challenges faced in data warehousing and analytics engineering, especially in regulated environments like finance. Being able to articulate your understanding of these challenges and potential solutions will demonstrate your strategic thinking.
✨Tip Number 4
Showcase any relevant experience with Agile methodologies, particularly if you've worked in Kanban or Scrum environments. This will illustrate your adaptability and readiness to thrive in a fast-paced setting, which is crucial for the role.
We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in analytics engineering, data modelling, and ETL projects. Use keywords from the job description to demonstrate that you meet the specific requirements of the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and how your skills align with the responsibilities outlined in the job description. Mention any experience with BigQuery, SQL, or data governance that makes you a strong candidate.
Showcase Relevant Projects: If you have worked on projects involving data warehousing or financial data, include these in your application. Describe your role, the technologies used, and the impact of your work to illustrate your capabilities.
Prepare for the Interview Process: Familiarise yourself with the interview stages mentioned in the job description. Be ready to discuss your technical skills and past experiences in detail, and prepare thoughtful questions to ask during your interviews.
How to prepare for a job interview at Referrals Only
✨Understand the Role
Make sure you have a solid grasp of what a Senior Analytics Engineer does, especially in relation to data modelling and ETL projects. Familiarise yourself with the specific tools mentioned in the job description, like BigQuery and SQL, as well as any relevant frameworks.
✨Prepare for Technical Questions
Expect to be asked about your experience with data warehousing concepts and your approach to building robust data models. Brush up on your technical skills and be ready to discuss past projects where you've successfully implemented data solutions.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss how you've identified and addressed challenges in previous roles. Think of examples where you've optimised processes or improved data quality, as this aligns with the company's focus on continuous improvement.
✨Engage with the Team's Values
Research Monzo's culture and values, particularly their commitment to collaboration and serving small businesses. Be ready to share how your personal values align with theirs and how you can contribute to their mission.
