Data Engineer Apprenticeship

Launch your career in data and technology. Gain hands-on experience in data engineering, cloud technologies, automation and dashboards while studying for a Level 4 DevOps Engineer Apprenticeship. Work on real projects that improve transport and public services, with expert mentoring, training and career development opportunities.

Requirements

• GCSE in: English (grade Grade C/4+)
• GCSE in: Maths (grade Grade C/4+)
• A relevant subject in: Level 3 A Level, T Level, Btec (grade Pass)
• Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
• Communication skills
• IT skills
• Attention to detail
• Organisation skills
• Problem solving skills
• Presentation skills
• Administrative skills
• Analytical skills
• Logical
• Team working
• Initiative
• Non judgemental
• Patience

Responsibilities

• Support the development and maintenance of data engineering solutions that help shape transport and public service decisions across the West Midlands
• Learn how to collect, transform and automate data using modern data engineering techniques and cloud technologies, including AWS
• Assist with the production of dashboards and reporting that provide valuable insights for strategic and operational decision-making
• Help maintain data systems and contribute to improving the quality, accessibility and security of organisational data
• Support the collection, analysis and management of transport, planning, social and economic data
• Work alongside experienced data engineers and colleagues across the organisation, gaining practical experience on a wide range of projects
• Contribute to the development of data solutions that support regional strategies, investment decisions and service improvements
• Communicate credibly with technical and non-technical people at all levels, using a range of methods; e.g. ‘Show and Tell’ and ‘Demonstrations’.
• Work within different organisational cultures with both internal and external parties
• Translate user needs into deliverable tasks, writing clear, concise and unambiguous user stories that the whole team can understand.
• Initiate and facilitate knowledge sharing and technical collaboration
• Deploy immutable infrastructure
• Install, manage and troubleshoot monitoring tools
• Navigate and troubleshoot stateful distributed systems, in order to locate issues across the end-to-end service.
• Work in agile, multi-disciplinary delivery teams, taking a flexible, collaborative and pragmatic approach to delivering tasks.
• Application of a range of cloud security tools and techniques - e.g. threat modelling, vulnerability scanning, dependency checking, reducing attack surface area - incorporating these tools and techniques into the automated pipeline wherever possible.
• Assess identified and potential security threats and take appropriate action based on likelihood v impact.
• Employ a systematic approach to solving problems, using logic and hypotheses / experimentation to identify the source of issues.
• Automate tasks where it introduces improvements to the efficiency of business processes and reduces waste, considering the effort and cost of automation.
• Engage in productive pair/mob programming.
• Write tests and follow Test Driven Development discipline in various different contexts.
• Release automation and orchestration as part of a Continuous Integration workflow and Continuous Delivery pipeline, automating the delivery of code from source control to the end users.
• Invest in continuous learning, both your own development and others, ensuring learning activities dovetail with changing job requirements. Keep up with cutting edge.
• Code in a general purpose programming language.
• Specify cloud infrastructure in an infrastructure-as-code domain-specific language.
• Interpret logs and metrics data within the appropriate context to identify issues and make informed decisions.
• Writing code in such a way that makes merging easier and facilitates branching by abstraction - i.e. feature toggling.
• Application of lightweight modelling techniques, such as whiteboarding, in order to gain consensus as a team on evolving architecture.
• Incremental refactoring by applying small behaviour-preserving code changes to evolve the architecture.