Analytics Engineer

Moneybox; City of London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A financial technology firm in London is seeking a Mid-Senior Level Data Engineer to join its Data and Insights team. The role involves designing data transformations, collaborating with analysts, and promoting best practices in a fast-paced environment. Ideal candidates will have 2-3 years of experience in analytics engineering, strong SQL skills, and a genuine interest in financial technology. Competitive salary and benefits offered.

Qualifications

• 2-3 years experience in analytics engineering handling large data sets.
• Experience delivering insights to stakeholders.
• Familiar with principles of modeling data warehouses.

Responsibilities

• Design and maintain automated data transformations.
• Collaborate with analysts to define and ship new analytic features.
• Promote analytics engineering practices within the team.

Skills

Analytics engineering

SQL

Automating data processes

Python

Data modeling

Financial Services experience

Git

CI/CD practices

Tools

Databricks

Snowflake

BigQuery

Power BI

dbt

Job description

At Moneybox, our mission is to give everyone the means to get more out of life. We're guided by our belief that wealth isn't about the money, it's about the means to more - more freedom, opportunities, possibilities, and peace of mind. Moneybox is an award-winning wealth management platform, helping over one and a half million people build wealth throughout their lives, whether they’re saving and investing, buying their first home, or planning for retirement.

About Moneybox

Moneybox is the award-winning app that helps you turn your money into something greater. We’ve brought saving, investing, home-buying, and retirement services all together into one simple app, so it’s easier than ever to achieve your goals and build wealth, whatever your starting point.

Job Brief

The Data and Insights team span everything from analytics engineering to reporting, insight analysis, decisioning, data science and machine learning. Helping everyone at Moneybox to understand what our customers are doing, how they are interacting with the app, which products they are using and what is important to them - this team ensures that we are equipped to deliver on our mission to help customers.

What you'll do

• Design, build and maintain our automated data transformations, to create analysis-ready datasets and sources of truth
• Architect and develop our data outputs at increasing scale, taking ownership over multiple data catalogs
• Collaborate with analysts and the wider business to understand their needs, and to define, design and ship new analytics features
• Help maintain code quality and organisation
• Promote the benefits of analytics engineering practices among the wider Insight Team

Who you are

• Genuinely interested in Moneybox and the services we offer
• Excited about being part of a fast growing company that's trying to make a positive mark on the world by helping everyone to reach their financial goals
• Excited about using data to answer questions, and particularly interested in the technical side of how to do this at increasing scale
• Loves to build tools that make your teammates’ jobs easier
• Somebody who thrives in a fast-paced startup environment
• Interested in all areas of the business and enjoys hearing about what other team members are working on
• Genuine interest in financial technology
• Constantly looking to improve in all areas that you can affect

Skills & Experience (Essential)

• 2-3 years experience in analytics engineering handling large data sets, delivering insight to stakeholders, or significant experience working closely with data analysts
• Experience with SQL (ideally within a modern data platform e.g. Databricks, Snowflake, BigQuery)
• Experience with automating data processes
• Familiarity with dbt (Cloud or Core)
• Understanding of Python
• Familiarity with delivering data to Power BI, or another modern BI platform
• Financial Services industry experience
• Experience with Git for writing, storing and collaborating on production level code
• Experience with the principles of modelling data warehouses (Gold, Silver, Bronze table structure, Kimball modelling etc)
• Experience working in a medium/large data team (20+)
• Applied knowledge of analytics engineering best practices and methodologies
• Knowledge of CI/CD

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Accounting/Auditing
• Financial Services and Data Infrastructure and Analytics

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