Experienced professionals who design, build, and maintain the data infrastructure that powers modern businesses. A critical role in ensuring data is accessible, reliable, and scalable.
Senior Data Engineers are the backbone of data infrastructure in organisations. They design, build, and maintain the systems that enable data to be collected, processed, and stored efficiently. These professionals work closely with data scientists, analysts, and other stakeholders to ensure that data is accessible and reliable. They are responsible for creating robust data pipelines, optimising data warehousing solutions, and implementing DataOps practices to streamline data operations. Whether in scaleups, research-heavy startups, or the larger consultancies, Senior Data Engineers play a crucial role in driving data-driven decision-making.
A typical week for a Senior Data Engineer is a mix of hands-on technical work and collaboration with cross-functional teams.
Based on advertised midpoints across the 217 UK listings priced in pounds in the last 12 months. Base salary only.
% of 186 listings posted in the last 12 months that mention each skill, extracted from job descriptions.
A typical UK progression for senior data engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.
Assists in the design and implementation of data pipelines and basic data warehousing solutions.
Takes ownership of specific data pipelines and contributes to the overall data infrastructure design.
Leads the design and implementation of complex data infrastructure, ensuring scalability and reliability.
Strategic leader in data infrastructure, driving innovation and best practices across the organisation.
There's no single route, but most people follow some version of these steps.
Start with a strong foundation in data engineering principles, including ETL/ELT processes, data warehousing, and SQL.
Work on real-world projects to build and maintain data pipelines, and collaborate with data scientists and analysts.
Deepen your expertise in areas like big data processing, DataOps, and cloud data infrastructure.
Take on leadership roles, managing data engineering projects and mentoring junior team members.
Influence the organisation's data strategy, driving innovation and best practices in data infrastructure.
Contribute to the broader data engineering community through speaking engagements, writing, and open-source contributions.
hireful London £75,000 – £85,000 pa
Owns the design and build of scalable data pipelines and data products on Databricks using PySpark, Spark SQL and Delta Lake, plus ETL/ELT development and enterprise data architecture. Works with Finance, Product, Sales, Marketing and Engineering stakeholders, embeds data quality and governance, and mentors a junior engineer in a small, high-impact team.
Ageas Insurance Limited Eastleigh £70,000 – £85,000 pa
Builds and supports data products on a modern cloud data platform, developing pipelines, integrations and orchestration with Databricks or Snowflake on AWS, Python, Spark, Airflow and SQL. Works in agile squads with data scientists, architects and product teams, supporting ML and GenAI infrastructure and promoting strong engineering standards.
The Alan Turing Institute London £57,000 – £69,000 pa
Designs and operates robust data pipelines that ingest, validate and structure large, heterogeneous datasets, and builds analyst-facing data products such as curated datasets, data models, serving layers and query interfaces. Establishes and maintains the data platform across cloud and on-premise environments, covering storage, compute, orchestration, access control and infrastructure-as-code, within Defence and partner security constraints. A senior individual contributor role setting data engineering standards, mentoring colleagues and shaping data architecture.
Reed Technology Guildford £55,000 – £75,000 pa
Designs, builds and optimises enterprise-scale data pipelines, ETL/ELT processes and lakehouse/warehouse solutions using Microsoft Fabric and Azure services. Works closely with analysts, developers and business stakeholders on data quality, governance and architecture, and mentors junior team members. Hybrid role with two days on-site.
Copello Birmingham £60,000 – £80,000 pa
Designs and maintains end-to-end data pipelines for large, complex datasets, transforming data into insights, analytical tools and dashboards. Works with software engineers, researchers and technical specialists on projects supporting national security infrastructure, with a focus on automation and process improvement in Linux-based environments.
Jackson Hogg Sunderland £55,000 – £65,000 pa
Builds and maintains ETL/ELT pipelines, integrating data from multiple systems and external providers into an Azure-based data estate. Develops scalable data models and improves monitoring, testing and platform performance while supporting data quality and governance. Works with data engineers, BI specialists and business stakeholders to deliver trusted reporting datasets.
Eclectic Recruitment Stevenage £45,000 – £55,000 pa
Designs enterprise-wide data and BI solutions for a defence organisation, integrating business data, simulators, missile test systems and shop-floor machines into governed, value-generating assets. Builds scalable ETL/ELT and streaming pipelines across MES/SCADA, ERP and PLM, and develops Power BI analytics for self-service and executive reporting. Works on data lakes, lakehouses and time-series stores with DataOps practices in hybrid/on-prem environments.
hireful Bristol £80,000 – £90,000 pa
Owns the design and build of scalable data pipelines and data products on Databricks using PySpark, Spark SQL and Delta Lake, plus ETL/ELT optimisation and enterprise data architecture. Partners with Finance, Product, Sales, Marketing and Engineering stakeholders, embeds data quality and governance, and mentors a junior engineer in a small, high-impact team.
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Key skills include expertise in ETL/ELT processes, data warehousing, SQL, and cloud data infrastructure. Strong problem-solving abilities and collaboration skills are also essential.
Common tools include Apache Kafka, Apache Spark, AWS Redshift, Google BigQuery, and Snowflake. Familiarity with programming languages like Python and SQL is also important.
The typical progression is from Junior Data Engineer to Data Engineer, then Senior Data Engineer, and finally Principal Data Engineer. Each step involves increasing responsibility and leadership.
For specific salary information, please refer to the salary section on this page.
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