Data Engineer

DF Capital Group

Manchester

Hybrid

GBP 60,000 - 90,000

Full time

4 days ago

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Benefits offered by this job

Private medical insurance

Private dental

Pension 10%

30 days leave

Gym membership

Discretionary bonus

Share awards

Life assurance

Income protection

SAYE

Cycle to work

Volunteer days

Modern offices in Ancoats

Job summary

DF Capital Group is seeking a Data Engineer to join the Data & Analytics team in Manchester. You will design and maintain scalable data pipelines, ingest data from internal systems and third-party services, and build robust ELT processes to support regulatory reporting, BI and analytics workloads.

The role focuses on Snowflake, DBT, Windmill, Python and GitHub in a regulated financial services environment. You will work in a small, agile team, taking ownership of end-to-end data lifecycle

Qualifications

Strong SQL skills with complex queries and data models.
Experience with cloud data architectures and platforms.
Experience sourcing data from relational databases and APIs.
Python for automation and data processing.
Knowledge of data warehousing concepts and dimensional modelling.
Experience with Git-based source control and CI/CD.

Responsibilities

Design, develop and maintain scalable data pipelines.
Build and optimise SQL-based solutions in Snowflake.
Create ELT processes to support reporting and analytics.
Develop data models for business and regulatory needs.
Ensure data quality and lineage across sources.
Collaborate with stakeholders on data requirements.

Skills

SQL

Python

Snowflake

DBT

Windmill

GitHub

CI/CD

Data quality

ETL

REST APIs

Tools

DBT

Windmill

Snowflake

.Streamlit

GitHub

Job description

We’re DF Capital – a specialist bank providing award-winning commercial finance, retail finance, and savings products to consumers and small businesses.

Based in Manchester, we serve thousands of customers across the UK and into Europe, supporting their ambitions with tailored financial solutions.

We help our customers realise their ambitions by doing things differently – combining the agility and innovation of a specialist lender with the security and service standards of a regulated bank. Whether it’s flexible lending structures or straightforward savings options, we focus on what matters most to our customers.

In 2025, we launched DF Capital Retail Finance – a subsidiary of DF Capital Bank Limited – to offer specialist hire purchase solutions to retail customers.

Our goal is simple: to do the absolute best for our customers, our communities, and each other.

Your new role:

We are seeking a Data Engineer to join our growing Data & Analytics team within a medium-sized UK bank. Working in a small, agile, you will play a key role in sourcing, integrating, transforming and delivering data from a variety of internal and external systems.

You will be responsible for building and maintaining scalable cloud-based data solutions, ingesting structured data from databases and operational systems, as well as semi-structured data from APIs and third-party services. Using Snowflake, DBT and Windmill, you will develop robust data pipelines that support regulatory reporting, operational processes, business intelligence and analytical workloads.

This role is well suited to an engineer who enjoys taking ownership, working across the full data lifecycle, and contributing to the continued development of a modern cloud data platform within a regulated financial services environment.

Data Engineering & Development

Design, develop and maintain scalable data pipelines and data integration solutions.
Build and optimise SQL-based solutions within Snowflake.
Create and maintain robust ELT processes supporting reporting and analytics requirements.
Develop and manage data models that support business, operational and regulatory needs.
Ensure data quality, consistency and integrity across multiple data sources.
Document data flows, transformation logic and technical solutions.

Data Integration & Ingestion

Design and maintain ingestion pipelines for both structured and semi-structured data.
Source and integrate data from operational databases, applications and third-party platforms.
Develop integrations with REST APIs and other external data services.
Extract, process and transform semi-structured data formats such as JSON and XML.
Monitor ingestion processes and implement controls to ensure data reliability and completeness.
Work with business and technical stakeholders to understand source systems and data requirements.

Data Transformation & Modelling

Build and maintain transformation layers using SQL and DBT.
Design reusable and scalable data models following engineering best practices.
Implement testing and validation to ensure high levels of data quality.
Optimise transformation performance and maintainability.

Platform Automation & Orchestration

Develop and maintain automated workflows using Windmill.
Schedule, orchestrate and monitor data processing activities.
Identify opportunities to improve operational efficiency through automation.
Support troubleshooting and resolution of production issues.

DevOps & CI/CD

Use GitHub for source control, collaboration and code reviews.
Support and improve CI/CD processes for data platform deployments.
Promote engineering best practices including version control, testing and release management.
Maintain technical documentation and operational runbooks.

Collaboration & Continuous Improvement

Work closely with the Lead Data Engineer and wider stakeholders across the bank.
Participate in architecture discussions and solution design.
Contribute to the evolution of the data platform and engineering standards.
Share knowledge and support continuous improvement initiatives within the team.

Essential Skills & Experience

Technical Skills

Strong SQL skills with experience developing complex queries, transformations and data models.
Experience working with modern cloud-based data architectures and data platforms.
Experience sourcing and integrating data from structured sources such as relational databases.
Experience working with semi-structured data including JSON, XML and API-based integrations.
Familiarity with Python for automation, scripting, API integration and data processing.
Experience designing and maintaining data transformation pipelines.
Good understanding of data warehousing concepts and dimensional modelling.
Experience working with Git-based source control and collaborative development practices.
Understanding of CI/CD principles and automated deployment processes.
Knowledge of data quality, testing and monitoring methodologies.

Professional Experience

Experience working as a Data Engineer, ETL Developer or similar role.
Experience delivering data solutions within a cloud environment.
Ability to work independently and manage priorities effectively.
Strong analytical and problem-solving skills.
Excellent communication skills with both technical and non-technical stakeholders.

Desirable Skills & Experience