Register Your Interest - Data Engineer Higher Apprenticeship

Build systems that collect, manage, and convert data into usable information for data scientists, data analysts and business intelligence analysts to interpret.

Occupational summary

Data Engineers build systems that collect, manage, and convert data into usable information for data scientists, data analysts and business intelligence analysts to interpret. A data engineer’s main aim is to make data accessible and valid so that an organisation can use it to evaluate and optimise their performance. The role of the data engineer is pivotal to any organisation; it ensures that data pipelines are established to support data scientists and other business stakeholders.

Knowledge

• Develop a deep understanding of how to build, monitor, and optimise data products and pipelines, ensuring performance, availability, and quality.
• Learn methods for moving, integrating, and normalising data, applying principles of data warehousing, governance, and security.
• Understand how to ensure compliance with regulations and support sustainable, cost-effective data solutions.
• Strengthen skills with cloud platforms, software development practices, metadata management, and data types.
• Gain insight into data product lifecycles, root cause analysis, business continuity, and best practices in service management.
• Evaluate prototypes, support continuous improvement, and communicate technical information effectively.

Skills

• Gather and refine user and business requirements to design scalable, efficient, and secure data products.
• Automate data pipelines, clean and validate data, and work across various data stores and formats.
• Query and manipulate data using tools like SQL and Python.
• Troubleshoot pipeline issues and ensure secure data system use.
• Create and maintain clear documentation, monitor data quality, and respond to incidents with root cause analysis and resolution.
• Collaborate with stakeholders, communicate effectively, and contribute to continuous improvement, including managing technical debt and advocating best practices.
• Assess and enhance existing data tools, support sustainable solutions, and stay current with new technologies and industry trends.

Behaviours

• Display proactive accountability by adapting to changing priorities and meeting deadlines.
• Work collaboratively with stakeholders, fostering inclusive, respectful relationships.
• Focus on quality and continuous improvement, using creativity and peer review to enhance data systems.
• Take personal responsibility for environmental sustainability and net zero outcomes.
• Use initiative and innovation to solve problems creatively and stay updated on emerging technologies to optimise sustainable data products and services.

Entry requirements

• Apprentices seeking to join the data pathway can speak to ATAC to determine which level will be most suitable for them, depending on prior experience and qualifications.

Progression routes

• Successful apprentices can progress onto higher-level data apprenticeships.

Key information

• Level (At end of programme): Level 5
• Maximum Duration: 17 months
• Available Funding: £19,000 funding band maximum available through the Apprenticeship Levy. Employers that do not pay the Levy will fund 5% of the funding band maximum.

Who's it for?

• Targeted towards individuals that collect, manage and build data into usable information for data scientists as part of their regular working role.

Recommended training provider(s)

• Cambridge Spark

Start date

• TBC

Register Your Interest

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