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Data Engineer Jobs

The backbone of modern data infrastructure. Building, maintaining, and optimising the pipelines that power data-driven decisions.

Open roles
192
Salary range
£30k – £130k
Hiring companies
106
View 192 live roles → Get an alert

Data Engineers are the architects and builders of the data infrastructure that underpins modern businesses. They design, build, and maintain the data pipelines, warehouses, and lakes that enable organisations to store, process, and analyse vast amounts of data. Whether working in scaleups, research-heavy startups, or the larger consultancies, Data Engineers play a crucial role in ensuring that data is accessible, reliable, and secure.

What the role does

A typical day for a Data Engineer

A typical week for a Data Engineer is a mix of coding, testing, and collaboration with cross-functional teams.

  1. 01
    Design and implement data pipelines using tools like Apache Kafka and Apache Spark.
  2. 02
    Optimise data storage and retrieval processes for efficiency and scalability.
  3. 03
    Collaborate with data scientists and analysts to understand their data needs.
  4. 04
    Monitor and maintain data infrastructure to ensure high availability and performance.
  5. 05
    Document and communicate data architecture and processes to stakeholders.
  6. 06
    Troubleshoot and resolve data-related issues as they arise.
Salary on the board

£30k – £130k

Based on advertised midpoints across the 137 priced listings posted in the last 12 months. Base salary only.

By seniority
£k base
Entry
30
38
1 job
Junior
35
41
2 jobs
Mid
35
113
57 jobs
Senior
40
100
39 jobs
Lead
40
110
12 jobs
Director
130
130
1 job
Career ladder

From Junior to Principal

A typical UK progression for data engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.

  1. Level 1

    Junior Data Engineer

    0–2 yrs

    Assists in building and maintaining data pipelines, with a focus on learning and supporting more senior team members.

  2. Level 2

    Data Engineer

    2–5 yrs

    Takes ownership of specific data pipelines and projects, ensuring they meet performance and reliability standards.

  3. Level 3

    Senior Data Engineer

    5–8 yrs

    Leads the design and implementation of complex data infrastructure, mentoring junior engineers and collaborating with cross-functional teams.

  4. Level 4

    Principal Data Engineer

    8+ yrs

    Strategises and oversees the entire data infrastructure, driving innovation and best practices across the organisation.

Pathway

How to become a Data Engineer

There's no single route, but most people follow some version of these steps.

  1. 1

    Learn the Basics

    Start with foundational skills in SQL, Python, and data storage systems. Gain experience with ETL processes and data warehousing.

  2. 2

    Build Pipelines

    Work on building and maintaining data pipelines using tools like Apache Kafka and Apache Spark. Focus on efficiency and scalability.

  3. 3

    Optimise Infrastructure

    Optimise data storage and retrieval processes to ensure high performance and reliability. Collaborate with data scientists and analysts.

  4. 4

    Lead Projects

    Take ownership of complex data infrastructure projects. Mentor junior engineers and ensure best practices are followed.

  5. 5

    Strategise and Innovate

    Strategise the overall data infrastructure, driving innovation and best practices. Oversee the implementation of new technologies and methodologies.

Live jobs

192 live roles

See all 192 roles →

Data Engineer

The Data Engineer will design, develop, and optimize enterprise data platforms to support data-driven decision-making in a financial services firm. Responsibilities include building ETL/ELT pipelines, ensuring data quality, and collaborating with business stakeholders and developers to deliver scalable data solutions. The role involves working with SQL, Python, and cloud platforms like Azure or AWS, and contributing to continuous improvement in data architecture and processes.

Noir Switzerland, United Kingdom £87,291 – £113,478 pa
Hybrid Permanent

Data Engineer

This role involves designing and building scalable, cloud-first data platforms to drive innovation and data-led decision-making. You will work across the full data lifecycle, from engineering secure, high-performance pipelines to managing data warehouses and lakes, ensuring regulatory compliance, and delivering high-quality datasets for analytics and AI initiatives.

Lynx Recruitment London, United Kingdom £40,000 – £85,000 pa
On-site Permanent

Fabric Data Engineer

This role involves designing, building, and maintaining scalable data pipelines within Microsoft Fabric Lakehouse environments. You will develop and optimize data ingestion and transformation workflows, create Python and PySpark processes, and support Power BI reporting and semantic models. As a senior member of the BI and data team, you will guide development standards, mentor developers, and ensure data solutions are scalable and aligned with enterprise data governance practices.

Tenth Revolution Group Cardiff, Cymru / Wales, CF10 2AF, United Kingdom £60,000 – £70,000 pa
Remote Permanent

Data Engineer – Azure Data Platform

This role involves designing and developing ETL/ELT pipelines within Azure, building scalable data ingestion and transformation solutions, ensuring data quality and performance, and collaborating with cross-functional teams to deliver data-driven insights. The focus is on automation and optimization of data workflows using Azure technologies.

FinTop Consulting London, United Kingdom £40,000 – £70,000 pa
Hybrid Permanent

Staff Data Engineer

As a Staff Data Engineer, you will lead the development and evolution of a cloud-native data platform, driving large-scale data transformations. Your responsibilities include designing and building robust data solutions, mentoring a team of data engineers, and making high-impact technical decisions. You will collaborate closely with Product and Delivery teams to deliver high-value, scalable data solutions and champion the adoption of modern cloud technologies.

Sanderson London, United Kingdom £80,000 – £99,000 pa
Hybrid Permanent

Fabric Data Engineer

Fabric Data EngineerUp to £70,000I am seeking an experienced Data Engineer to support the design, development and optimisation of modern cloud-based data platform within a global manufacturing organisation specialising in the production of high-quality equipment.Sitting within a global data and...

Tenth Revolution Group Bristol, United Kingdom £60,000 – £70,000 pa
Permanent

Senior Data Engineer

This role involves designing, building, and maintaining scalable cloud-based data pipelines using Microsoft technologies like Azure Data Factory, Azure Synapse, Databricks, and Microsoft Fabric. You will collaborate with data engineers, BI developers, analysts, and process engineers to ensure data solutions align with business goals and best practices, while also supporting the productionisation of machine learning models and large language models.

Robert Walters Cheshire, United Kingdom £65,000 – £75,000 pa
Hybrid Permanent

Senior Data Engineer

This Senior Data Engineer role involves designing, building, and maintaining scalable data pipelines using AWS services. You'll work closely with platform engineers, analysts, and data scientists to migrate an existing data warehouse to AWS, implement data quality checks, and contribute to the modern data lakehouse architecture. The role offers opportunities to influence the platform's architecture and provide technical guidance to junior engineers.

SRG Manchester, United Kingdom £70,000 – £80,000 pa
Hybrid Permanent
See all 192 roles →
Top hirers

Companies hiring data engineers

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Hiring locations

Where this role is hiring

The locations with the most live listings for this role today.

London

Location
53 open

Manchester

Location
17 open

Birmingham

Location
10 open

Leeds

Location
7 open

Bristol

Location
5 open

Cardiff

Location
4 open
FAQs

Common questions

  • Data Engineers commonly use tools like Apache Kafka, Apache Spark, SQL, Python, and data warehousing solutions such as Amazon Redshift or Google BigQuery.

  • Collaboration with data scientists is crucial. Data Engineers need to understand the data needs of data scientists to build effective data pipelines and infrastructure.

  • Key skills include proficiency in SQL, Python, and data storage systems, as well as a strong understanding of ETL processes, data warehousing, and big data technologies.

  • The typical career progression is from Junior Data Engineer to Data Engineer, then Senior Data Engineer, and finally Principal Data Engineer, with increasing levels of responsibility and leadership.

  • For specific salary information, please refer to the salary section on this page, which is updated with the latest data from live job listings.

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