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Cloud Data Engineer Jobs

Specialists who design, build, and maintain data infrastructure in the cloud. Essential for scaling data operations and ensuring robust data pipelines.

Open roles
0
Salary range
£55k – £86k
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Cloud Data Engineers are the backbone of modern data infrastructure, focusing on building, maintaining, and optimising data pipelines and storage solutions in cloud environments. They work with platforms like AWS, Azure, and GCP to ensure data is efficiently processed, stored, and accessible. These roles are in high demand across tech scaleups, research-heavy startups, and the larger consultancies, where robust data infrastructure is crucial for business growth and innovation.

What the role does

Inside the role of a Cloud Data Engineer

A typical week for a Cloud Data Engineer is split between designing and implementing data pipelines, troubleshooting issues, and collaborating with cross-functional teams.

  1. 01
    Design and implement data pipelines using cloud services.
  2. 02
    Optimise data storage and retrieval processes for efficiency.
  3. 03
    Troubleshoot and resolve data infrastructure issues.
  4. 04
    Collaborate with data scientists and analysts on data requirements.
  5. 05
    Monitor and maintain data security and compliance.
  6. 06
    Document and communicate data infrastructure changes and improvements.
Salary on the board

£55k – £86k

Based on advertised midpoints across the 19 priced listings posted in the last 12 months. Base salary only.

Salary visibility
19% of listings advertise a salary — up from 0% the year before.
By seniority
£k base
Mid
55
86
9 jobs
Senior
55
119
8 jobs
Skills & tools

What hiring managers ask for

% of 15 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

SQL
87%
Python
67%
ETL
67%
Azure
33%
Databricks
33%
AWS
33%
PySpark
33%
Data Pipelines
33%
Azure Data Factory
33%
Data Governance
27%
Data Warehousing
27%
Azure Synapse Analytics
27%
Career ladder

From Junior to Principal

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

  1. Level 1

    Junior Cloud Data Engineer

    0–2 yrs

    Assists in the design and implementation of basic data pipelines and storage solutions, with guidance from senior team members.

  2. Level 2

    Cloud Data Engineer

    2–5 yrs

    Takes ownership of designing and implementing complex data pipelines, ensuring data is efficiently processed and stored.

  3. Level 3

    Senior Cloud Data Engineer

    5–8 yrs

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

  4. Level 4

    Principal Cloud Data Engineer

    8+ yrs

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

Pathway

How to become a Cloud Data Engineer

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

  1. 1

    Learn cloud fundamentals

    Gain a solid understanding of cloud platforms like AWS, Azure, and GCP, and their core services.

  2. 2

    Build data pipelines

    Start designing and implementing basic data pipelines, focusing on ETL/ELT processes and data warehousing.

  3. 3

    Optimise and scale

    Enhance your skills in optimising data storage and processing, and learn to scale data infrastructure efficiently.

  4. 4

    Lead projects

    Take on leadership roles in large-scale data infrastructure projects, mentoring junior engineers and collaborating with cross-functional teams.

  5. 5

    Drive innovation

    Strategise and drive innovation in data infrastructure, implementing best practices and new technologies.

No Cloud Data Engineer Jobs jobs right now

We don't have any matching roles at the moment, but new jobs are added daily.

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FAQs

Common questions

  • Key skills include proficiency in cloud platforms (AWS, Azure, GCP), experience with data pipelines and ETL/ELT processes, and strong problem-solving abilities.

  • Certifications like AWS Certified Data Engineer, Azure Data Engineer Associate, and Google Cloud Professional Data Engineer are highly valued in the industry.

  • A Cloud Data Engineer focuses on building and maintaining data infrastructure, while a Data Scientist focuses on analysing and modelling data to derive insights.

  • Common tools include Apache Kafka, Apache Spark, AWS Glue, Azure Data Factory, and Google BigQuery.

  • Salaries for Cloud Data Engineers can vary widely based on experience and location. For specific salary ranges, please refer to the salary section on this page.

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