Summary

This is an exciting opportunity within our York Delivery Centre. The right candidate will be joining alongside a number of other analysts at the same level and given the opportunity to work across a number of areas.

Wage

£20,000 a year

£20,000 - £22,000 per annum

Training course

Data engineer (level 5)

Hours

9.00am - 5.00pm, Monday to Thursday (office based), Friday will be working from home.

37 hours 30 minutes a week

Start date

Wednesday 21 October 2026

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

Client engagements - working as part of a Finyx team on digital, data & technology programmes and projects.
Sales - assisting in the identification of potential opportunities and supporting the creation of bid responses.
Service line development – aiding in the creation of materials that will help us to sell and to deliver our consulting services.
Internal initiatives – contributing to the ongoing growth of Finyx; improving internal processes and contributing to our Corporate Social Responsibility (CSR) and Inclusion, Diversity and Equality (I,D&E) agendas.

Where you'll work

THE CATALYST
BAIRD LANE
YORK
YO10 5GA

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

This programme combines live workshops, self-paced learning, and on-the-job application.

Learners are supported by a dedicated Digital Learning Consultant (DLC) and follow QA’s “Discover, Practise, Apply” methodology.

Requirements

Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.

Skills

Communication skills
Attention to detail
Organisation skills
Problem solving skills
Team working

Other requirements

Entry requirements:

A Level 3 qualification in a relevant area in any grade
Acceptable qualifications include, any of:
Two A levels in one or more similar subject.*
Level 3 apprenticeship in a similar subject.
International Baccalaureate at Level 3 in a similar subject
BTEC Extended Diploma in a similar subject.
Experience with programming languages (such as Python)

OR equivalent work experience:

2-3 years in a similar subject-related role.

*'Similar subject' relates to areas directly relevant to or commensurate with 'Digital and Technology Solutions'. Typically this would be areas such as but not limited to Level 3 digital apprenticeships, A-Level/BTEC Computer Science, Information Technology, Networking, Software Engineering, etc.

Please note: Learners must not hold an existing qualification at the same or higher level than this apprenticeship in a similar subject.

You may also have a combination of qualifications and experience which demonstrate the minimum foundation needed for the programme. In this instance you could still be considered for the programme.

If you hold international equivalents of the above qualifications, at the time of your application you must be able to provide an official document that states how your international qualifications compare to the UK qualifications.

For more information please visit the UK ENIC website.

Data Engineer Apprentice

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