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

Apply Now

Analytics Data Engineer

McCabe & Barton
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Analytics Data Engineer – Snowflake & DBT (Contract)

Data Engineer (Analytics & Data)

Principal Data Engineer - Azure Databricks (Unity Catalog) - Contract

Principal Data Engineer - Azure Databricks (Unity Catalog)

Data Engineer, Prime Video Core Analytics and Tooling

Principal Data Engineer - Azure Databricks (Unity Catalog)

Analytics Data Engineer
Location:

London (Hybrid/Remote available)
Salary:

£45,000 - £70,000 based - on experience

The Opportunity
A leading Financial Services organisation is seeking exceptional Analytics Data Engineers to join their ambitious Data Transformation initiative. This is a permanent role offering competitive compensation and flexible working arrangements.
As an Analytics Data Engineer, you will be at the forefront of their data transformation, designing and delivering data products that empower business teams with self-service analytics capabilities. You'll leverage cutting-edge technologies, including Snowflake, Power BI, Python, and SQL to create scalable, intuitive data solutions that drive business value.

Key Responsibilities
Build Data Products:

Collaborate with business domains to design and develop ETL/ELT pipelines and dimensional models optimised for Power BI
Drive Governance:

Define and enforce data ownership, quality, and security standards within the Data Mesh architecture
Enable Self-Service:

Create intuitive data models and provide training to empower business users to explore data independently
Own the Data Lifecycle:

Take end-to-end responsibility for data products, from conception to deployment and continuous improvement
Champion Innovation:

Stay current with the latest trends and advocating for best practices across the organisation

The Ideal Candidate
We're looking for a curious, organised, and outcome-driven professional with a passion for data and collaboration. You should bring:
Technical Expertise:

Proven experience coding ETL/ELT pipelines with Python, SQL, or ETL tools, and proficiency in Power BI, Tableau, or Qlik
Data Modelling Skills:

Strong knowledge of dimensional modelling and database principles
Governance Experience:

Track record of working in democratized data environments, establishing controls and guardrails
Collaboration & Communication:

Ability to work effectively with senior stakeholders, present data solutions, and guide business users
Problem-Solving Mindset:

Exceptional analytical skills to tackle complex data challenges and deliver reliable, high-performance code

If you are open to exploring this role further, please respond to this advert with your latest CV for review.

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.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.