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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
174
Salary range
£30k – £240k
Hiring companies
95
View 174 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

£30k – £240k

Based on advertised midpoints across the 295 priced listings posted in the last 12 months. Base salary only.

By seniority
£k base
Entry
30
38
1 job
Junior
30
45
8 jobs
Mid
30
113
113 jobs
Senior
44
240
98 jobs
Lead
40
240
37 jobs
Director
95
130
4 jobs
Skills & tools

What hiring managers ask for

% of 222 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

SQL
70%
Python
70%
AWS
33%
Azure
32%
Data Modelling
31%
CI/CD
27%
Data Pipelines
27%
Data Governance
26%
ETL
25%
Databricks
23%
PySpark
18%
Data Warehousing
18%
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

174 live roles

See all 174 roles →

Lead Data Engineer (Snowflake)

This role involves leading end-to-end data engineering initiatives on modern cloud platforms, with a focus on designing data solutions, building ingestion pipelines, and developing transformations and data models. The engineer will work on greenfield projects from design through deployment and optimisation, using infrastructure-as-code tools and collaborating directly with stakeholders. The position offers full ownership of delivery in a fully remote UK-based setup.

Harnham - Data and Analytics Recruitment Nottingham, United Kingdom £75,000 – £90,000 pa
Remote Permanent

Lead Data Engineer (Snowflake)

Lead Data Engineerup to £90,000 + BENEFITSFully Remote (UK)This is a great opportunity to join a high-growth organisation where you can take ownership of end-to-end data engineering delivery across modern cloud platforms and greenfield projects.THE ROLE:You will take ownership of...

Harnham - Data and Analytics Recruitment Cardiff, Cymru / Wales, CF10 2AF, United Kingdom £75,000 – £90,000 pa

Senior Data Engineer / GCP / Looker / Big Query

Senior Data Engineer / GCP / Looker / Big Query£(Apply online only) per day (Outside IR35)London / HybridSenior Data Engineer / GCP / Looker / Big QueryThis is an opportunity for you to join a rapidly growing ecommerce business who...

TRIA London, United Kingdom

Senior Data Engineer

Pontoon is an employment consultancy. We put expertise, energy, and enthusiasm into improving everyone's chance of being part of the workplace. We respect and appreciate people of all ethnicities, generations, religious beliefs, sexual orientations, gender identities, and more. We do...

Pontoon Warwick, United Kingdom
Experis logo

Finance Data Engineering Lead

This role involves developing and deploying finance and actuarial data pipelines using Python and PySpark within a cloud data environment. You will build datasets and models for reporting, integrate with existing data frameworks, and collaborate with design and architecture teams to deliver aligned solutions.

Experis London, United Kingdom £750 – £950 pd
Hybrid Contract
Adecco logo

Lead Data Engineering (Hands-on Python / Databricks)

Lead the design and development of a greenfield data platform using Databricks, Python, and PySpark, with a balance of hands-on engineering and technical leadership. Drive best practices in scalable ETL/ELT pipelines and Lakehouse architecture while mentoring engineers and collaborating with stakeholders across a high-profile financial sector programme.

Adecco London, United Kingdom
Hybrid Contract

Senior Data Platform Engineer

This role involves designing, building, and operating a cloud-native data platform on AWS using infrastructure as code and CI/CD pipelines. The engineer will support a modern Lakehouse architecture, embed security and governance controls, and collaborate with data and AI teams to deliver trusted data products. Focus is on reliability, observability, cost efficiency, and scalable data ecosystems.

Microlise Langley Mill, Derbyshire, NG16 4BS, United Kingdom £55,000 pa
Hybrid Contract

Senior Data Platform Engineer – Central London

The role involves working on enterprise-level data pipelines using modern technologies like Python, SQL (dbt), Azure Functions, and Azure DevOps. You will help drive improvements to the data platform and contribute to the company's growth and technical direction.

Ada Meher Mayfair, London, W1K 3DN, United Kingdom £75,000 – £85,000 pa
Hybrid Permanent
See all 174 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
48 open

Manchester

Location
11 open

Birmingham

Location
7 open

Leeds

Location
6 open

Newcastle

Location
3 open

Coventry

Location
3 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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