Data Engineering and Analytics Apprenticeship Programme

St. James’s Place
Cirencester
3 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst Higher Apprenticeship

Data Analyst Higher Apprenticeship

Level 5 Data Engineer Apprentice

Data Engineer

Data Analyst - 12 Month Student Placement

Data Engineer I - QuantumBlack, AI by McKinsey

Who We Are

St. James's Place (SJP) is a leading Wealth Management company which works in partnership to plan, grow and protect our clients’ financial futures. We deliver personalised, face-to-face financial advice to our clients, who trust us to manage their money to reach their goals.

The Data Engineering and Analytics Apprenticeship Programme

Assessment Centre: Tuesday 17 Feb 2026

The Data Engineering and Analytics Apprenticeship Programme within our CTO Function is a 12-month programme and offers an excellent grounding in the fundamental principles of Data in one of the UK’s largest wealth management organisations.

The Chief Data Office (CDO) sits within our Chief Technology Office (CTO) and ensures data is managed as one of the organisation’s most valuable assets. It sets the vision for how data is used, ensures information is accurate, well-managed, and secure, and helps the business unlock value through insights and innovation.

As an apprentice in this area, you’ll be exposed to:

  • Data governance and quality – learning how we make sure data is trusted and consistent.
  • Data management – understanding how data is stored, integrated, and shared across the business.
  • Analytics and insight – understand how data is turned into meaningful information that guides decisions. Learn how to develop and deploy visualisations.
  • Regulation and compliance – gaining awareness of how data is protected and used responsibly.
  • Data culture – helping improve awareness and skills so everyone can make better use of data.

Alongside this you will be studying for Level 5 Data Engineer Apprenticeship

You will also advance your technical skills through a curriculum developed for our apprentices and delivered through our St James’s Place Technology and Data Academy.

This is a permanent vacancy and so upon successful completion of the Apprenticeship Programme you will continue your career within our Chief Data Office (CDO).

Key Responsibilities

  • Learn and apply data engineering fundamentals – gain hands-on experience with databases, cloud platforms, and data integration tools.
  • Support data pipelines – help design, build, and maintain processes that move and transform data between systems.
  • Assist with data quality checks – monitor data for accuracy, completeness, and consistency, escalating issues where needed.
  • Work with senior engineers – shadow and support in developing efficient, reliable, and secure data solutions.
  • Document processes and standards – contribute to clear documentation to support knowledge sharing and best practice.
  • Collaborate across teams – work with analysts, architects, and business users to understand data needs and deliver value.
  • Develop technical skills – grow your knowledge in SQL, Python, cloud technologies (e.g., AWS, Azure, or Snowflake), and modern data engineering tools.
  • Support data governance initiatives – help apply data security, compliance, and management standards.

Requirements of the Job:

We are looking for someone with an interest of basic knowledge of data analytics and engineering who is willing to learn and progress within the profession and undertake the apprenticeship qualification.

  • On track to complete or have attained A-levels (or equivalent) in Computing, Data or analytical subject(s)
  • Minimum Level 5 in English Language and Mathematics at GCSE (or equivalent)
  • Understanding of Databases
  • Great analytical skills.
  • Strong communication- written and verbal.
  • Self-motivated and interested in learning and taking on a challenge.

Special Requirements:

This role will be based full-time in our Cirencester office and you will be expected to be In the office a minimum of three days per week.

Please note that due to the eligibility criteria for visa sponsorship, we are unable to offer work visa sponsorship for our Apprenticeship programmes.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.