The Data and AI School of London is an NCFE approved centre for this qualification (NCFE Account No. 11001657). Enrol below to begin your learning journey.
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Level 5 · NCFE
Enrolling now NCFE Approved Qualification number 610/5972/9

NCFE Level 5 Diploma: Data Engineer - HTQ

A Higher Technical Qualification building advanced skills to design, build and manage the data systems behind modern organisations.

Duration: Self-paced online study; typically one to two years

Level
Level 5
Qualification number
610/5972/9
Awarding organisation
NCFE
Regulated status
On the RQF, regulated by Ofqual
Delivery
100% online
Study pattern
Self-paced online study; typically one to two years
NCFE This qualification is awarded by NCFE and regulated by Ofqual
NCFE Account No. 11001657

Course overview

This is a Higher Technical Qualification (HTQ), approved by the Institute for Apprenticeships and Technical Education to meet specific employer needs and industry requirements. Its content has been aligned with the Data Engineer apprenticeship standard, and it is designed for learners who want to begin or advance their career within data engineering.

Made up of mandatory units, the qualification covers core data engineering concepts including data structures, storage, integration and governance, with learners exploring structured and unstructured data and database normalisation. Assessment combines an internally assessed portfolio of evidence with task-based assessments, graded pass, merit or distinction.

It is well suited to those looking to move into or progress within data engineering roles, or to further their studies in the digital sector at a higher level.

What you will study

The units below, their unit reference numbers and their guided learning hours are taken directly from the NCFE qualification specification.

Unit Title Unit reference Hours
01 Data engineering principles and foundations
6 learning outcomes
  1. Explore the principles of data
  2. Explore the concepts of data governance
  3. Explore and apply the principles of normalisation and redundancy in databases
  4. Explore approaches to data
  5. Explore the unique features and of different data formats
  6. Explore common data development frameworks and architectures
K/651/6932 90
02 Data architecture and management
5 learning outcomes
  1. Explore and analyse the inherent data collection and usage
  2. Explore frameworks for data quality contributing dimensions support
  3. Develop a data product that complies regulatory requirements
  4. Explore the principles of data
  5. Analyse relevant policies and to ensure business continuity when implementing data solutions
L/651/6933 70
03 Data pipelines and automation
4 learning outcomes
  1. Explore approaches used for storing data
  2. Explore the application of data one location to another
  3. Explore deployment methods for pipelines and automated processes
  4. Explore the types and uses of common engineering tools and applications
M/651/6934 110
04 Software development for data products
5 learning outcomes
  1. Explore the principles of software for data products
  2. Analyse how to cost and build a align with organisational sustainability responsibilities
  3. Explore the appropriate use of service management in relation to data products
  4. Explore the processes for evaluating implementing prototypes within a production
  5. Explore the lifecycle of implementing solutions within a business
R/651/6935 110
05 Data analytics, business intelligence and incident management
4 learning outcomes
  1. The application of data analysis industry
  2. Analyse the use of on- demand cloud services to meet requirements
  3. Explore the processes used to monitor optimise the performance of a data product
  4. Explore advanced data interrogation
T/651/6936 90
06 Professional practice and continuous improvement in data engineering
4 learning outcomes
  1. Explore the principles of sustainable products and environmental, and governance responsibilities
  2. Analyse approaches to continuous improvement and how this can be of benefit to an organisation
  3. Explore areas of advancement data collection, handling and management to support organisational operations
  4. Explore the common methods and techniques used to communicate with stakeholders organisations
Y/651/6937 70
Total guided learning hours 540

Entry requirements

  • No specific prior skills or knowledge required, though a relevant Level 4 qualification is helpful.
  • Learners must be at least 18 years old.
  • Sound English and maths skills are recommended given the technical nature of the course.
Take it with you

The course guide

Everything on this page as one document you can keep, print, or send to whoever is deciding with you.

  • All 6 units, with the hours behind each one
  • How you are assessed, and who checks the marking
  • How paying works, and what is due when
  • Entry requirements and where the qualification leads
Download the guide (PDF)

Generated from this qualification's record, so the units and hours in it are the ones on this page. The fee is here on the page rather than in the guide, so a saved copy cannot quote you an old one.

How you are assessed

Your work is assessed by our qualified assessors, internally quality assured, and externally quality assured by NCFE. Assessment is against the criteria published in the qualification specification, and your assessor tells you what is needed before you start each unit.

For what happens after you submit: who marks it, who checks the marking, how long feedback takes and what to do if you disagree with a decision, see how assessment works.

If you need an adjustment to how you are assessed, for a disability or any other reason, ask us before you begin. We arrange adjustments under our Reasonable Adjustments policy, and you can request one online.

How we assess and quality assure is set out in DAIS-POL-016 Assessment and Internal Quality Assurance.

How you study, and what you need

You study online through our virtual learning environment, which is where the teaching material, your assessment submissions, your feedback and your progress all live. You work at your own pace, with tutor support throughout. Everyone completes a short online induction before starting an assessed unit.

What you need to take part
Device Laptop or desktop computer
Operating system Windows 10 or macOS 10.15 or later
Browser Google Chrome or Mozilla Firefox, latest version
Internet speed 10 Mbps download and 5 Mbps upload
Webcam Required for live sessions and identity verification
Microphone Required for live sessions

These are the minimum requirements published in DAIS-POL-024 Online Learning and Digital Delivery.

Support, and how quickly we reply

These are the response times we commit to in policy, not an aspiration.

What How Response
General questions Message your tutor in the VLE Within 2 working days
Assessment feedback Returned in the VLE or e-portfolio Within 10 working days of submission
Technical problems Technical support email Within 1 working day
Urgent welfare concerns Email to the Designated Safeguarding Lead Within 1 working day

Published in DAIS-POL-024 and DAIS-POL-009 Learner Support.

Registration and your certificate

We register you with NCFE before you begin any assessed unit, and we collect your Unique Learner Number as part of that. When your assessment decisions are finalised and quality assured, we claim your certificate through the NCFE portal and you are notified digitally. The certificate comes from NCFE, not from us.

Set out in DAIS-POL-008 Learner Registration and Certification.

Progression

Learners who achieve this qualification could progress to the following:

  • employment:
    • data engineer
    • machine learning engineer
    • data architect
    • ETL developer
  • further education:
    • related apprenticeships
  • higher education:
    • data science degree.

Common questions

Who awards NCFE Level 5 Diploma: Data Engineer - HTQ, and how do I get my certificate?

NCFE Level 5 Diploma: Data Engineer - HTQ is awarded by NCFE, an Ofqual-approved awarding organisation, and sits on the Regulated Qualifications Framework (RQF). The qualification number is 610/5972/9. The Data and AI School of London is an NCFE approved centre (Account No. 11001657). We register you with NCFE before you start any assessed unit and collect your Unique Learner Number. Once your work is assessed and quality assured we claim your certificate through the NCFE portal, and it is issued by NCFE rather than by us.

What do I need before I can start?

No specific prior skills or knowledge required, though a relevant Level 4 qualification is helpful. We assess every applicant individually and will tell you if a different level would suit you better.

Can I study this entirely online?

Yes. Teaching, materials and assessment are all delivered through our Moodle-based virtual learning environment, so you can study from anywhere in the UK. You need a laptop or desktop computer, a current version of Chrome or Firefox, and a broadband connection of at least 10 Mbps down and 5 Mbps up. Tutor support is available throughout, and we answer questions within 2 working days and return assessment feedback within 10 working days of submission.

Can I enrol now, and when do I pay?

The fee is £3,495. Enrolment is open, so you can apply online today. Nothing is paid at application: payment is taken only after you accept an offer.

Not sure this is the right qualification?

Ask before you apply. We will say honestly if a different level would suit you better.

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