Remote Senior Analytics Engineer in Southampton

Remote Senior Analytics Engineer in Southampton

Southampton Full-Time 50000 - 60000 £ / year (est.) Home office (partial)
Grabjobs

At a Glance

  • Tasks: Build and optimise data models to enhance our Data Warehouse for impactful decision making.
  • Company: Join Monzo, a forward-thinking tech company with a focus on innovation and collaboration.
  • Benefits: Flexible working hours, £1,000 learning budget, and the option for part-time work.
  • Other info: Dynamic team environment with opportunities for continuous improvement and career growth.
  • Why this job: Make a real difference in data-driven decision making while working with cutting-edge technology.
  • Qualifications: Experience in SQL, data modelling, and a passion for Big Data and ETL projects.

The predicted salary is between 50000 - 60000 £ 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 Big Query) 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.

Grabjobs

Contact Details:

Grabjobs Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Remote Senior Analytics Engineer in Southampton

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Grabjobs!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Remote Senior Analytics Engineer at Grabjobs.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Grabjobs.

Apply Directly through Our Website

When you find a suitable opening like Remote Senior Analytics Engineer at Grabjobs, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Remote Senior Analytics Engineer in Southampton

SQL
Problem-Solving Skills
Communication Skills
Python
Data Engineering
Data Pipeline Development
API Integration

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Grabjobs, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Grabjobs. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Grabjobs

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Grabjobs!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.