FATP · an independent directoryApprenticeship data sourced from DfE, ESFA and IfATEUpdated daily · GB
L5Apprenticeship7461 approved provider
The Level 5 Data engineer, and the 1 provider delivering it.
Build systems that collect, manage, and convert data into usable information for data scientists, data analysts and business intelligence analysts to interpret.
About this apprenticeship
What this apprenticeship covers
Apprentices learn to design, build, and maintain data pipelines that move information reliably between systems. The programme covers ETL (Extract, Transform, Load) processes, data normalisation, SQL and NoSQL databases, and Python or similar programming languages. Apprentices develop skills in data quality assurance, governance, security compliance, and technical documentation. They also learn to gather requirements from stakeholders, automate data flows, troubleshoot pipeline failures, and assess the performance of data products against business needs.
Day-to-day responsibilities
On a typical week, an apprentice might write and test ETL scripts, query databases using SQL or Python, and investigate data quality issues flagged by analysts or scientists. They will document pipeline designs, communicate outages or access problems to affected teams, and attend requirement-gathering meetings with business stakeholders. Work is often split between independent technical tasks and collaboration with data analysts, data scientists, software engineers, and data architects, depending on the organisation's structure and project stage.
Career outlook
Completion typically leads to a confirmed data engineer role, with progression into senior or lead data engineer positions over time. From there, common paths include data architect, analytics engineering, or machine learning operations. Employers hiring for this role span a wide range of sectors: central and local government, the NHS, financial and professional services, retail, and technology companies. Organisations with large or complex data estates are the most frequent hirers, particularly those investing in business intelligence, reporting infrastructure, or data science capability.
1 approved provider
Sorted by achievement rate.
Cambridge Spark
Employer: 4.0
Cambridge Spark is a specialist data and AI training provider that helps corporate and government or...
Career outcomes
Roles after completion
Completers typically move into a Data Engineer role, either within the organisation where they trained or with a new employer. Some take on titles such as Junior Data Engineer or Associate Data Engineer in larger teams, while others step straight into a mid-level Data Engineer position in smaller organisations. Day-to-day responsibilities include building and maintaining ETL pipelines, managing data stores, writing SQL and Python scripts, and supporting data analysts and data scientists with clean, accessible data.
Progression paths
Within three to five years, many data engineers move into a Senior Data Engineer position, taking ownership of pipeline architecture and mentoring junior team members. From there, two tracks tend to open up. The leadership track leads toward Data Engineering Manager or Head of Data Engineering. The specialist track moves toward Data Architect, where the focus shifts to designing the broader data infrastructure a business runs on, or toward a Machine Learning Engineer role for those working closely with data science teams.
Where these roles sit
Government departments, NHS trusts and local authorities hire data engineers to handle large administrative datasets and support analytical and reporting functions. In the private sector, financial services firms, insurers, retailers and technology companies are consistent employers. Consultancies place data engineers across multiple client sectors. Roles exist at every scale, from small product businesses with a single data team to large enterprises running complex, multi-system data platforms.
How it's assessed
How the apprenticeship is assessed
Throughout the apprenticeship, learners build knowledge and practical skill while working in a real data engineering role, covering areas such as pipeline design, ETL processes, data quality, governance, and stakeholder communication. Before moving to final assessment, the apprentice must pass a readiness point, commonly called the gateway, where the employer and training provider confirm that the apprentice has demonstrated sufficient competence across the required knowledge, skills, and behaviours. Final assessment then confirms the apprentice can perform the role to the standard expected. Assessment models across many standards are currently being updated, so check the standard's gov.uk page for the current specification.
What learners need to prepare
Building a strong body of evidence from real work is the most practical thing an apprentice can do throughout the programme. That means keeping records of pipeline builds, data quality decisions, technical documentation, and stakeholder interactions as they happen, rather than trying to reconstruct them later. Regular reviews with both the employer and training provider will help track progress against the knowledge, skills, and behaviours required, and give early warning of any gaps that need addressing before the gateway.
Choosing a provider
What good looks like
Look for providers with an achievement rate above 65% on their FATP profile, and check whether their apprentice and employer satisfaction scores are both above 80%. For a data engineering standard, the curriculum should visibly cover ETL pipeline development, SQL and Python, cloud data platforms (such as AWS, Azure or GCP), and version control workflows. Ask whether teaching staff hold current practitioner experience, not just historical credentials. Providers who can point to alumni working in data engineering roles after completion, and who run cohorts with employers in data-heavy sectors such as finance, government or retail, are likely to offer more relevant real-world exposure.
Red flags to watch for
Be cautious if a provider has high learner volumes but a declining achievement rate, particularly if they cannot explain why. Vague answers about which tools and platforms apprentices actually work with during training are a concern; if the curriculum does not reference current data stack technologies by name, it may be outdated. Providers who cannot distinguish this standard from a data analyst apprenticeship, or who bundle generic digital content in place of pipeline engineering and data architecture work, are unlikely to develop the technical depth the role requires.
Questions to ask before you commit
- What tools and cloud platforms do apprentices work with during training, and how recently has the curriculum been updated to reflect changes in the data engineering market?
- How do you structure the ETL and pipeline automation elements of the programme, and do apprentices build and deploy working pipelines as part of their learning?
- What is your current achievement rate for this standard, and how has it changed over the past two years?
- Can you show examples of the kinds of projects or end-point assessment evidence previous apprentices have produced?
- How do you handle apprentices whose employers use different tech stacks, for example one using Azure and another using GCP?
- What employer engagement does the provider offer beyond the off-the-job training, such as reviews, progress check-ins, or skills gap analysis?
- How many apprentices do you currently have on this standard, and what is the typical cohort size?
Common questions
What entry requirements do employers and learners need to meet for this apprenticeship?
There are no nationally mandated entry requirements set by the standard, so employers set their own criteria. In practice, most employers look for some prior experience or qualifications in IT, mathematics, or a related field, and a good level of English and maths. Apprentices must be employed for the duration of the programme. If a candidate already holds a qualification at the same or higher level in a closely related subject, their eligibility should be checked against the funding rules before enrolment.
How much time does the apprenticeship take, and how does learning fit around the job?
The typical duration is around 24 months, though this depends on the individual's prior experience and the employer's programme design. Apprentices are employed throughout and apply their learning directly in their role, covering areas such as building data pipelines, ETL scripting, and data quality management. Current rules on minimum duration and off-the-job training hours are subject to revision under ongoing Skills England reforms. Check the current funding rules on gov.uk for the most up-to-date requirements before setting up a programme.
How is the apprenticeship assessed, and what does gateway involve?
Before taking end-point assessment, the apprentice must pass through a gateway, where the employer and training provider confirm that the apprentice has met all knowledge, skills, and behaviour requirements and is ready to be assessed. Assessment models for many standards are currently being reviewed as part of Skills England reforms, so the specific end-point assessment methods may change. Check the current assessment plan on gov.uk for the most accurate picture of what the apprentice will need to demonstrate to achieve the standard.
How does an employer pay for this apprenticeship, and what does it cost?
The funding band for this standard is £19,000, which is the maximum that can be drawn from the apprenticeship levy or government co-investment to cover training and assessment costs. Levy-paying employers use funds from their digital apprenticeship service account. Employers who do not pay the levy co-invest, contributing 5% of the training cost while the government pays the remaining 95%. Employers with fewer than 50 staff taking on an apprentice aged 16 to 18 pay nothing, with the government covering the full cost.
What does a data engineer apprentice actually do day to day?
Day-to-day work typically includes building and maintaining data pipelines, writing ETL scripts to extract, transform, and load data between systems, and querying databases using SQL and Python. Apprentices clean and validate data, troubleshoot pipeline failures, and maintain technical documentation. They liaise with data analysts, data scientists, and business stakeholders to understand data requirements, and they monitor the performance of data systems to ensure data is accurate, accessible, and delivered on time.
What can a data engineer do after completing this apprenticeship?
Completion leads to the occupational title of data engineer and a Level 5 qualification. From there, common progression routes include senior data engineer roles, data architecture, or moving into data science or machine learning engineering. Some completers go on to study for degree-level apprenticeships or other higher qualifications in data, software engineering, or computer science. The skills gained, particularly around pipeline automation, data governance, and cloud-based data tools, are transferable across sectors including financial services, healthcare, government, and technology.
Not sure which provider fits?
Tell us a bit about your team and we'll send a shortlist.
Need help choosing a provider?
Tell us your requirements and we'll match you with the right training providers.
Curated by Alex Lockey, FATP founder and editor. Last reviewed: .
Sources include the apprenticeship's official specification on apprenticeships.gov.uk, Skills England guidance, IfATE archive records, DWP funding bands, and provider data sourced directly from the public Apprenticeship Provider and Assessment Register (APAR). Standard reference: 746.
Some sections on this page were drafted with AI assistance from published source data and reviewed by a human editor before publication. See our editorial methodology for how we maintain this content. Spotted something out of date? Tell us.
Related standards
Software Developer L4Artificial intelligence (AI) and automation practitioner L4Hardware, network and infrastructure foundation apprenticeship L2Infrastructure technician L3Digital product manager L4Software and data foundation apprenticeship L2Information communications technician L3Network Cable Installer L3