Data Quality Engineer

Funding Circle UK; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Competitive salary

Benefits

Job summary

Funding Circle is seeking an Analytics Engineer / Data Quality Engineer to shape our Data Quality approach and build the data foundations for high growth areas. This role sits in London with a hybrid work pattern and offers a competitive salary plus benefits.

You will build high quality dbt models, enforce data quality rules, and collaborate with data analysts and scientists to improve data accuracy and governance.

Qualifications

• Strong SQL skills with efficient, well-structured queries.
• Experience with DBT and modular data models.
• Experience in Data Quality engagements.
• Knowledge of dimensional modelling.
• Experience with AWS data services (S3, Athena, Glue).

Responsibilities

• Building and owning high quality dbt models, ensuring they are performant, well documented and thoroughly tested.
• Rule Engineering: Translate business logic into programmatically enforced Data Quality Rules.
• Collaborate with analysts and data scientists to understand their needs and build models that drive Data Quality and the visibility and measurability of Data accuracy.
• Champion best practices for Data Quality and data testing across data engineering teams.
• Review and work on Data Quality issues, both technically and by root cause analysis with stakeholders.

Skills

SQL

DBT

Data Quality

Dimensional Modelling

Data Quality Metrics

AWS Data Services

Data Lakes/Warehouses

Problem Solving

AI Solutions

Tools

Great Expectations

dbt tests

Elementary

Soda

Deequ

Job description

We’re on a mission to back the UK’s small businesses like no one else

Small businesses are the backbone of the economy, and we’re here to help them win. We’ve built a platform that uses clever data to get them the funding they need in minutes, not weeks.

At Funding Circle, we have the restless energy of a fintech start-up with the stability of a public company. It’s a unique mix that gives Circlers the autonomy to take ownership and the scale to make an impact that truly counts.

We’re a high-performing team that chooses to lift each other up. We challenge, we champion, and we have each other’s backs - because we know that when we stand together, we move faster and build better.

The impact is real: Last year alone, the businesses on our platform generated £7.2bn for the UK economy

Come and join a mission that matters!

The role

London (Hybrid) | 2 days in the office | Competitive Salary + Benefits

We’re looking for an Analytics Engineer / Data Quality Engineer to join our team and help shape our approach to Data Quality and work on the data foundations for high growth areas at Funding Circle.

This is a unique opportunity to help build a top tier Data Quality and Data Governance function, with the full backing of the business. We’re investing heavily in the people, tools, and technology needed to make it happen - and giving you the chance to play a key role in shaping its future.

Hear from our Senior Data Product Manager, Michael, about what it's like to be part of our Data team!

Your Responsibilities Will Include

• Building and owning high quality dbt models, ensuring they are performant, well documented and thoroughly tested
• Rule Engineering: Partner with product engineering and business teams to translate business logic into programmatically enforced Data Quality Rules
• Collaborate with analysts and data scientists to understand their needs and build models that drive Data Quality and the visibility and measurability of Data accuracy.
• Champion best practices for Data Quality and data testing, across data engineering teams
• Review and work on Data Quality issues, both from a technical perspective and performing root cause analysis with stakeholders

What we’re looking for

• Strong SQL skills, with experience writing efficient and well structured queries
• Hands on experience with DBT, building and maintaining modular, scalable data models that follow best practices
• Previous experience working on Data Quality engagements
• Strong understanding of dimensional modelling
• Strong understanding of Data Quality and how it is measured
• Desireable: Experience writing complex validation logic using tools like Great Expectations, dbt tests, Elementary, Soda, or Deequ.
• Familiarity with AWS data services ( S3, Athena, Glue )
• Experience working with data lakes or modern data warehouses ( Snowflake, Redshift, BigQuery )
• A pragmatic problem solver who can balance technical excellence with business needs
• Able to architect custom AI solutions and smart automated systems that are safe, maintainable, and aligned with our long-term mission
• Act as a technical bridge and mentor, training “builders