Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer Apprentice

Abri Group
Eastleigh
4 days ago
Create job alert

As our new Data Engineer Apprentice, you'll learn and apply how reporting solutions are used for effective data visualisation and strategic and operational reporting. You'll work closely with our team to develop the technical and soft skills required to gain hands on experience to build and manage a modern data stack.


Responsibilities

  • Develop the skills to assist in designing, developing and maintaining Extract, Transform and Load (ETL) pipelines for data ingestion and transformation
  • Work with databases and data lakes to clean, structure, integrate and optimised datasets and data models
  • Collaborate with business/data analysts and stakeholders to understand datasets and reporting requirements, gaining the skills to be able to articulate data solutions to stakeholders in a way that can be easily understood
  • Understand and apply core data principles, practices and standards to ensure data accuracy, integrity, and security within the reporting environment
  • Analyse and interpret data sets to extract meaningful insights, trends, and patterns
  • Explore and document the data lifecycle and how this is applied within Abri with regards to data collection processes, ensuring data accuracy, completeness, and reliability, 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 elevate 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 and qualifications

  • The apprenticeship training will take place online and you'll be working from our Eastleigh office a minimum of three days per week to connect and collaborate with colleagues
  • The other two days can be worked from at a place of your choosing whether that's at another of our offices, a cafe or at home
  • A Level in: Preferably Maths & other related subjects (IT) (grade C). 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
  • Customer care skills
  • Problem solving skills
  • Presentation skills
  • Number skills
  • Analytical skills
  • Team working

Abri is a large housing provider who own and manage more than 58,000 homes and various community assets, serving around 113,000 customers across the South of England. We believe everyone has the right to a good quality safe, warm and sustainable home in a community where they can belong, grow and thrive. What does that look like in real terms? We're investing £689m over the next ten years in our existing homes to improve building safety and make them more energy efficient. We're delivering 10,000 homes by 2030, ensuring affordable housing is built where it's needed most. We're investing in our communities, to address local issues and create opportunities for everyone. As we grow, we're re-establishing our strong local presence to provide a really good service. Abri has adopted a regional approach to service delivery, with our operating areas split into three, each with their local governance and leadership. This will ensure our colleagues are more visible.


28 days holiday. Generous pension scheme with contributions up to 10% Life assurance of 5x your annual salary. Generous parental & family leave. Health and wellbeing packages. Electric car scheme. Flexible working.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer Apprentice

Data Engineer Apprentice: Build Modern Data Pipelines

Data Engineer Apprentice - Hybrid Learning & Growth

Data Engineering and Analytics Apprenticeship Programme

Apprentice Data Engineer

Data Engineer I - QuantumBlack, AI by McKinsey

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.