Engineering Manager (Data Engineering)

Compare the Market
Peterborough
3 days ago
Create job alert
Overview

Data Engineering Manager
Function: Tech
Location: Hybrid, London or Peterborough

Curious about what’s next? So are we. Join Compare the Market and help to make financial decision making a breeze for millions. At Compare the Market, we’re a purpose-driven business powered by tech and AI. We’re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.

We’ve carved a meerkat-shaped niche and we’re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you’ll fit right in. We’d love you to be part of our journey.

Responsibilities
  • Data Engineering Managers at Compare the Market facilitate technical discussions with Engineers and Staff Engineers to help the team identify simple, effective solutions to complex problems. They support and empower Engineers to lead technical initiatives that improve engineering practices and team maturity. You will continuously assess and improve team processes to enhance delivery and alignment with agile principles.
  • You’ll focus on the professional development of team members through coaching, mentoring, and feedback, fostering personal growth and ownership. Support the hiring and retention of top engineering talent, and champion the company’s values both within technology and across the organisation.
  • High Performance Culture: empower autonomous decision-making within teams by removing barriers and fostering a culture of ownership and accountability, driving continuous improvement and using data-driven insights to optimise team performance.
  • People Leadership: oversee performance of direct reports, developing and retaining high performing talent, and supporting hiring and retention of top engineering talent while championing company values.
  • Delivery & Task Performance: drive performance by establishing key metrics, collaborating with Product Managers and Technology Delivery Managers to ensure delivery aligns with the technical roadmap and company strategy, while maintaining high operational standards for the systems the team owns.
  • Stakeholder Management and Communication: engage with stakeholders across CtM to ensure transparency, alignment, and effective communication of technical and strategic goals, bridging the gap between technical teams and non-technical stakeholders.
  • Team Leadership: facilitate technical discussions among engineers, remove impediments, promote collaboration, and continuously improve team processes to align with agile principles.
  • Incident Management, Operational Excellence: take ownership of incident management, ensuring timely resolution and minimal disruption to services, and manage escalation processes with swift, effective resolutions.
What We’d Like To See From You
  • Experience leading data engineering teams building modern data platforms or large-scale data pipelines and supporting agile teams.
  • Strong understanding of streaming and batch data processing architectures, ideally including technologies such as Kafka, Databricks, orchestration frameworks, and dbt.
  • Skilled in driving continuous improvement using data-driven techniques.
  • Strong analytical, facilitation, negotiation, and organisational skills.
  • Experienced in coaching teams to adopt agile principles and practices.
  • Solid technical understanding, able to bridge technical and non-technical discussions.
  • Skilled in aligning cross-functional teams and managing stakeholder expectations.
  • Leads through influence, fostering accountability and trust.
  • Actively shares knowledge and promotes learning within teams and communities.
  • Strong interpersonal skills, fostering collaboration and understanding.
Why Compare the Market?

We’re a business built for pace and performance. Here, you’ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress. We believe diverse teams make better decisions, and we’re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive. If you’re ready to stretch yourself, raise the bar, and grow with a team that’s serious about performance, innovation, and purpose, we’d love to hear from you.


#J-18808-Ljbffr

Related Jobs

View all jobs

Engineering Manager - MLOps & Analytics

Data Engineering Manager

Data Engineering Manager (Pricing)

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

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.

Careers

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.

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.

🍪 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.