Summary
We’re on the lookout for an Apprentice Data Engineer to join our team in September 2026 for 24-months.
This is a great opportunity to start your career, gaining hands-on experience while working towards a recognised Level 5 Data Engineer apprenticeship standard.
Wage
Competitive
Competitive wage offered
a competitive salary of £24,454 per annum
Training course
Data engineer (level 5)
Hours
Monday - Friday, times to be confirmed.
37 hours a week
Start date
Monday 14 September 2026
Duration
2 years
Positions available
1
Work
Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.
What you'll do at work
As an Apprentice Data Engineer, you will support the design, development, and maintenance of data systems that enable the organisation to make informed decisions regarding housing services and operations.
Working within an on-site Microsoft SQL Server environment, you will help manage data pipelines, integrate systems using APIs, and ensure data is accurate, accessible, and secure.
You will gain hands on experience with tools such as SSMS, SSIS, and MuleSoft, while also contributing toward the organisation’s transition toward modern cloud technologies such as Microsoft Fabric.
You’ll learn on the job while getting involved in:
* Assisting in building and maintaining ETL (Extract, Transform, Load) processes using SSIS to move and transform data across systems
* Working with SQL server (via SSMS) to query, clean, and manage large datasets
* Supporting API integrations using MuleSoft to connect internal and external systems
* Monitoring data quality, troubleshoot issues, and ensure data reliability for reporting and analytics
* Collaborating with analysts and business teams to understand data requirements and deliver solutions
* Gaining exposure to emerging technologies, including Microsoft Fabric, as the organisation evolves its data platform
Where you'll work
You can select which locations you want to apply for in your application on Find an apprenticeship.
This apprenticeship is available in these locations:
* Country House, 27 Longfield Road, South Church Enterprise Park, Bishop Auckland, DL14 6XB
* Spectrum 6, Spectrum Business Park, Seaham, Durham, SR7 7TT
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
QA LIMITED
Training course
Data engineer (level 5)
What you'll learn
Course contents
* Collate, evaluate and refine user requirements to design the data product.
* Collate, evaluate and refine business requirements including cost, resourcing, and accessibility to design the data product.
* Design a data product to serve multiple needs and with scalability, efficiency, and security in mind.
* Automate data pipelines such as batch, real-time, on demand and other processes using programming languages and data integration platforms with graphical user interfaces.
* Produce and maintain technical documentation explaining the data product, that meets organisational, technical and non-technical user requirements, retaining critical information.
* Systematically clean, validate, and describe data at all stages of extract, transform, load (ETL).
* Work with different types of data stores, such as SQL, NoSQL, and distributed file system.
* Identify and troubleshoot issues with data processing pipelines.
* Query and manipulate data using tools and programming such as SQL and Python. Manage database access, and implement automated validation checks.
* Communicate downtime and issues with database access to stakeholders to mitigate the operational impact of unforeseen issues.
* Evaluate opportunities to extract value from existing data products through further development, considering costs, environmental impact and potential operational benefits.
* Maintain a working knowledge of data use cases within organisations.
* Use data systems securely to meet requirements and in line with organisational procedures and legislation.
* Identify new tools and technologies and recommend potential opportunities for use in own department or organisation.
* Optimise data ingestion processes by making use of appropriate data ingestion frameworks such as batch, streaming and on-demand.
* Develop algorithms and processes to extract structured data from unstructured sources.
* Apply and advocate for software development best practice when working with other data professionals throughout the business. Contribute to standards and ways of working that support software development principles.
* Develop simple forecasts and monitoring tools to anticipate or respond immediately to outages and incidents.
* Identify and escalate risks with suggested mitigation/resolutions as appropriate.
* Investigate and respond to incidents, identifying the root cause and resolution with internal and external stakeholders.
* Identify and remediate technical debt, assess for updates and obsolescence as part of continuous improvement.
* Develop, maintain collaborative relationships using adaptive business methodology with stakeholders such as, business users, data scientists, data analysts and business intelligence teams.
* Present, communicate, and disseminate messages about the data product, tailoring the message and medium to the needs of the audience.
* Evaluate the strengths and weaknesses of prototype data products and how these integrate within an organisation’s overarching data infrastructure.
* Assess and identify gaps in existing tools and technologies in respect of implementing changes required.
* Identify data quality metrics and track them to ensure the quality, accuracy and reliability of the data product.
* Selects and apply sustainable solutions to contribute to net zero and environmental strategies across the various stages of product and service delivery.
* Horizon scanning to identify new technologies that offer increased performance of data products.
* Implement personal strategies to keep up to date with new technology and ways of working.
* Collate, evaluate and refine user requirements to design the data product.
* Collate, evaluate and refine business requirements including cost, resourcing, and accessibility to design the data product.
* Design a data product to serve multiple needs and with scalability, efficiency, and security in mind.
* Automate data pipelines such as batch, real-time, on demand and other processes using programming languages and data integration platforms with graphical user interfaces.
* Produce and maintain technical documentation explaining the data product, that meets organisational, technical and non-technical user requirements, retaining critical information.
* Systematically clean, validate, and describe data at all stages of extract, transform, load (ETL).
* Work with different types of data stores, such as SQL, NoSQL, and distributed file system.
* Identify and troubleshoot issues with data processing pipelines.
* Query and manipulate data using tools and programming such as SQL and Python. Manage database access, and implement automated validation checks.
* Communicate downtime and issues with database access to stakeholders to mitigate the operational impact of unforeseen issues.
* Evaluate opportunities to extract value from existing data products through further development, considering costs, environmental impact and potential operational benefits.
* Maintain a working knowledge of data use cases within organisations.
* Use data systems securely to meet requirements and in line with organisational procedures and legislation.
* Identify new tools and technologies and recommend potential opportunities for use in own department or organisation.
* Optimise data ingestion processes by making use of appropriate data ingestion frameworks such as batch, streaming and on-demand.
* Develop algorithms and processes to extract structured data from unstructured sources.
* Apply and advocate for software development best practice when working with other data professionals throughout the business. Contribute to standards and ways of working that support software development principles.
* Develop simple forecasts and monitoring tools to anticipate or respond immediately to outages and incidents.
* Identify and escalate risks with suggested mitigation/resolutions as appropriate.
* Investigate and respond to incidents, identifying the root cause and resolution with internal and external stakeholders.
* Identify and remediate technical debt, assess for updates and obsolescence as part of continuous improvement.
* Develop, maintain collaborative relationships using adaptive business methodology with stakeholders such as, business users, data scientists, data analysts and business intelligence teams.
* Present, communicate, and disseminate messages about the data product, tailoring the message and medium to the needs of the audience.
* Evaluate the strengths and weaknesses of prototype data products and how these integrate within an organisation’s overarching data infrastructure.
* Assess and identify gaps in existing tools and technologies in respect of implementing changes required.
* Identify data quality metrics and track them to ensure the quality, accuracy and reliability of the data product.
* Selects and apply sustainable solutions to contribute to net zero and environmental strategies across the various stages of product and service delivery.
* Horizon scanning to identify new technologies that offer increased performance of data products.
* Implement personal strategies to keep up to date with new technology and ways of working.
Training schedule
Data Engineer Level 5.
Requirements
Essential qualifications
GCSE in:
* English (grade 4)
* Maths (grade 4)
Level 3 A (level)/ BTEC in:
Digital/Computer Science (grade 3)
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
Skills
* Communication skills
* IT skills
* Organisation skills
* Problem solving skills
* Analytical skills
* Logical
* Team working