Analytics Data Engineer

McCabe & Barton
London
7 months ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer - ETL, Analytics & Data Quality

Performance Data Engineer: Build Scalable Analytics Data Products

Marketing Analytics Data Engineer | ML, Python & SQL

Senior Data Engineer

Lead Data Engineer – Compute Data Platform

Lead Data Engineer – Compute Data Platform

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.

Jobs

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.

Careers Jobs

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.

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.