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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
153
Salary range
£40k – £100k
Hiring companies
81
View 153 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

Inside the role of 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

£40k – £100k

Based on advertised midpoints across the 584 UK listings priced in pounds in the last 12 months. Base salary only.

Salary visibility
16% of listings advertise a salary — up from 0% the year before.
By seniority
£k base
Entry
28
41
6 jobs
Junior
30
56
19 jobs
Mid
40
85
177 jobs
Senior
50
100
183 jobs
Lead
54
118
65 jobs
Director
95
126
5 jobs
Skills & tools

What hiring managers ask for

% of 389 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
68%
SQL
67%
Data Modelling
37%
AWS
32%
Data Pipelines
32%
Azure
31%
ETL
30%
Data Governance
29%
CI/CD
27%
Databricks
21%
Data Warehousing
20%
Power BI
19%
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

153 live roles

See all 153 roles →

Senior Data Engineer (Databricks)

Build and optimize scalable data pipelines in Databricks to unify marketing, CRM, and paid media data into a centralized lakehouse. Collaborate with analytics and marketing teams to develop data models supporting dashboards, attribution, and marketing mix modeling. Work in a greenfield environment to establish a single source of truth across diverse data sources.

Lawrence Harvey Uxbridge, London, UB8 1SB, United Kingdom £69,000 – £72,000 pa

Senior Data Engineer

Design and build data pipelines for an enterprise ERP migration project, focusing on ETL development, SQL optimization, and Python-based automation within an AWS environment. Work iteratively using Jira to support data engineering tasks aligned with SAP/S4 HANA integration. Contribute to evolving automation initiatives as the project progresses.

Brio Digital Leeds, West Yorkshire, United Kingdom £500 – £550 pd

GCP Data Engineer

Design and build scalable data applications and ETL pipelines on Google Cloud Platform, using Python, Go, and BASH. Develop cloud-native services, automate infrastructure with Terraform and Ansible, and maintain CI/CD pipelines. Work across BigQuery, Pub/Sub, and Dataflow to deliver production-grade data solutions in a media and broadcasting environment.

83zero Isleworth, London, TW7 7AL, United Kingdom £525 – £550 pd

Fabric Data Engineer

The role involves building and enhancing data pipelines within Microsoft Fabric's live production environment, focusing on transforming CRM data into actionable insights. You'll work with PySpark, SQL, and Data Factory to modernize legacy systems while collaborating closely with stakeholders to identify data gaps and improve data quality. The position offers hands-on involvement in automation, pipeline optimization, and the ongoing migration to a Fabric-first data platform.

Tenth Revolution Group London, United Kingdom £55,000 – £65,000 pa
Hybrid Permanent

Fabric Data Engineer

Design and build scalable data pipelines on Microsoft Fabric within a greenfield transformation project, enabling enterprise-wide analytics and reporting. Establish modern data architecture and best practices in a growing data team with direct influence on technical direction. Work with Delta Lake and lakehouse architectures to deliver production-ready datasets supporting strategic business decisions.

Tenth Revolution Group Bury, United Kingdom £55,000 pa

Data Platform Engineer

This role involves managing and developing a complex Snowflake and Azure data platform ecosystem, building self-service capabilities, and automating platform provisioning and operational processes. You will work closely with engineers, architects, and data teams to improve platform reliability, monitoring, and observability.

ALTERED RESOURCING LTD London, United Kingdom £70,000 – £75,000 pa
Experis logo

Lead Data Engineer

The Lead Data Engineer will develop, maintain, and quality assure numerical models for calculating pEPR fees and producer payments. They will lead the data strategy, ensuring robust and transparent processes, and collaborate across teams to support decision-making and policy development.

Experis London, United Kingdom £600 – £678 pd
Remote Contract Clearance Required
Experis logo

Lead Azure Data Engineer

This role involves designing, building, and optimizing a large-scale Azure Data Platform, including data ingestion, ETL/ELT pipelines, and scalable data warehousing. You'll lead the development of robust data solutions, implement CI/CD, and ensure data quality and governance.

Experis United Kingdom £650 – £675 pd
Remote Contract Clearance Required
See all 153 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
43 open

Manchester

Location
14 open

Leeds

Location
8 open

Oxford

Location
8 open

Birmingham

Location
7 open

Bristol

Location
5 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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