Data Engineer Apprentice

Summary

Architect, build, and maintain scalable, high-performance data pipelines. Contribute to building data observability tools to ensure data quality, consistency, and availability across the organisation. Optimise processes to support data ingestion, transformation, and warehousing.

Wage

£23,000 a year

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Training course

Data engineer (level 5)

Hours

8.30am - 5pm (1-hour lunch break), working days TBC

37 hours 30 minutes a week

Start date

Tuesday 20 May 2025

Duration

1 year 9 months

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

Architect, build, and maintain scalable, high-performance data pipelines
Contribute to building data observability tools to ensure data quality, consistency, and availability across the organisation
Optimise processes to support data ingestion, transformation, and warehousing
Work closely with Data Analysts, Data Scientists and Software Engineers to build, automate and refine data products which solve business problems
Support client delivery for analytics engineering projects (these projects may involve elements of data analysis and data science)

Where you’ll work

St. Pauls House
23 Park Square South
Leeds
LS1 2ND

Training

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

College or training organisation

QA LIMITED

Your training course

Data engineer (level 5)

Equal to higher national diploma (HND)

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.

Your training plan

This training plan has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.

More training information

Introducing QA’s brand-new Level 5 Data Engineer apprenticeship programme, meticulously designed to provide learners with a strong foundation for the development of advanced technical competencies, enabling comprehensive professional and personal growth.

This specialised apprenticeship curriculum comprehensively covers essential knowledge and skills crucial for the proficient design, development and management of intricate data systems.

Learners will be equipped to skilfully architect, administer, and transform data into actionable insights tailored for consumption by Data Scientists, Data Analysts, and Business Intelligence professionals, empowering organisations to drive innovation, optimise business processes, and catalyse informed decision-making.

A natural progression having completed this programme would be onto our Degree Apprenticeship Programme data pathway.

This apprenticeship is designed to produce Data Engineers with the skills to build systems which collect, manage, and convert data into valuable information for data scientists, data analysts and business intelligence analysts to interpret and translate into business impact.

The Data Engineer L5 apprenticeship blends online learning, face-to-face workshops and on-the-job experience to transform learners into highly skilled tech professionals.

Who is it a good fit for?

Existing Data Engineers looking to upskill
Data Analysts looking to move into an Engineering role
Database Administrators

As part of their programme learners will complete:

7 learning knowledge modules teaching theory and practical application. These are primarily taught online and are supported by classroom training workshops.

Work-based portfolios & projects will be completed at work, over the course of the programme to demonstrate practical abilities.

Optional Microsoft Certification

As part of the Level 5 Data Engineer Apprenticeship, learners will be able to access Cloud Academy resources which will prepare them for taking the optional Microsoft Certification exam.

Requirements

Desirable qualifications

A Level in:

Two in relevant subject (grade Any)

BTEC in:

Similar subject (grade Any)

Other in:

Similar subject (grade Any)
Similar subject (grade Any)

Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.

Skills

IT skills
Attention to detail
Problem solving skills
Team working

Other requirements

About QA: Our apprenticeships are the perfect way to gain new skills, earn while you learn, and launch yourself into an exciting future. With over 30,000 successful apprenticeship graduates, we're a top 50 training provider, dedicated to helping you succeed. Interested? Apply now!

About this company

Hyperfinity leverage cutting edge data science and AI to support retailers in making profitable decisions regarding pricing, marketing, and retail media, combining innovative technology with expert human insights to deliver exceptional results for their clients. HyperFinity was established to help retailers and brands use advanced analytics to understand customer and product relationships, and make unified, customer led decisions, with the insight they uncover. Hyperfinity have a growing list of esteemed partners including household names such as Morrisons, Costa Coffee, Hotel Chocolat, Card Factory, Toolstation, and JD Sports.

Company benefits

Early finish every Friday. Casual dress code. ‘Lunch and learn’ and on-demand online courses. Quarterly team building/away days. One charity day each year. Discounted gym memberships (Nuffield, Hussle+) AXA Health Insurance - private healthcare

After this apprenticeship

To qualify as a fully-fledged Data Engineer at Level 5 and continue your growth at HyperFinity with strong progression plans in place.

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