Engineering Manager (Data Engineering)

Compare the Market
Peterborough
2 weeks 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 Big Data

Data Engineering Manager

Data Engineering Manager

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.