Senior Data Engineering Manager

myGwork - LGBTQ+ Business Community
Manchester
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer - £62,000 - Hybrid

Digital Data Consultant, Data Architecture, Data Engineering

Senior Machine Learning Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Join to apply for the Senior Data Engineering Manager role at myGwork - LGBTQ+ Business Community.


This job is with Booking.com, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.


N.B. This role does not come with relocation assistance; therefore candidates must be currently based in the UK in order to be considered.


Job Title: Senior Data Engineering Manager


Location: Manchester, UK


Role Overview

The Trips Senior Data Engineering Manager (SEM) at Booking.com plays a pivotal leadership role, accountable for the Data Engineering Managers (direct reports) and their respective teams. This position involves leading all aspects of the engineering function within their reporting line, providing technical guidance and input, ensuring sound engineering procedures consistent with Booking.com standards, and ensuring strong, sustainable delivery.


This Data SEM reports to the Director of Data and is a member of the Trips Data Function leads team contributing to Strategy and impact of the end-to-end Trips Data Function.


Key Job Responsibilities And Duties

  • Impact and Leadership

    • Strategic Impact: The SEM leads, influences, and owns delivery within their track(s), ensuring the medium-term (1-2 year) technical viability and health of the tech estate in their domain. They foresee medium‑term business and technology trends, developing informed tech, people, and delivery plans, including budget management.
    • Delivery Impact: Partnering with stakeholders to create and execute the delivery roadmap for their track(s), capacity and skills planning, and critical risks and dependencies management. Data compliance and governance must be woven into design and culture, and the SEM is key to championing this. This role involves getting things done by taking ownership, being proactive, and collaborating with business counterparts and other stakeholders.
    • Level of Autonomy: The SEM is responsible for the entire technical strategy, roadmap, and delivery for one or more tracks or a Track Group, aligning their technical strategy with larger departmental and organizational goals.
    • Team Dynamics/Structure: Manages 4‑6 teams each led by a Data Engineering Manager (EMs), with a total team size typically ranging from 25‑50 individuals. The team construct can be a mixture of Managers and Individual Contributors (ICs). The SEM is also responsible for managing headcount, actively participating in recruitment, planning, and budgeting.
    • Organizational Health: Responsible for creating and leading diverse, psychologically safe, high‑performing teams, driving continuous improvement through metrics. The SEM is responsible for the collective data engineering delivery, reliability, resilience, and organizational health of all teams under their scope.


  • Technical Expertise and Guidance

    • End‑to‑End System Ownership: Owns services and data pipelines end‑to‑end by actively monitoring health and performance, setting relevant metrics, acting upon SLO breaches and security vulnerabilities. This includes reducing business continuity risks through state‑of‑the‑art practices and documentation like runbooks and reducing risk via continuous delivery and experimentation frameworks. Ensure teams are comfortable iteratively developing, owning, and monitoring cloud infrastructure.
    • Technical Incident Management: Addresses and resolves live production issues, mitigating customer impact within SLA, and improves system reliability through root cause analysis.
    • Building Data infrastructure, pipelines, apps and consumption assets: Possesses sufficient knowledge to build and maintain high‑quality data solutions using relevant languages, writing readable/reusable code, and ensuring data security and integrity.
    • Architectural Guidance: Advises product teams on technical solutions that meet functional, non‑functional, and architectural requirements, and sets a clear direction for technical capabilities by evaluating and aligning target architecture improvements. Deep technical expertise and thorough hands‑on experience in modern data engineering best practices are required, along with a strong understanding of cloud‑native data patterns and technologies (AWS preferred).


  • Communication, Coaching, and Mentoring

    • Delivers clear, well‑structured, and meaningful information tailored to the audience, achieving mutually agreeable solutions through adaptability and active listening.
    • Coaches, guides, and improves the overall performance of stakeholders and colleagues by sharing experience and knowledge. They have a proven track record of growing technical leaders and team members, facilitating the growth of Engineering Managers.


  • Continuous Improvement and Innovation

    • Identifies opportunities for process, system, and structural improvements, designing and implementing relevant changes.
    • Establishes best practices and innovates new groundbreaking enablers from the industry.
    • The role also emphasizes a commitment to Agile, Continuous Integration, and Continuous Delivery.



Role Qualifications And Requirements

  • Demonstrable experience of leading Data Engineering Managers / Team Leads
  • Demonstrable experience shaping data product and provisioning from conception through to delivery at scale
  • Demonstrable experience of working in Agile environments and, more importantly, an Agile culture and ethos
  • Demonstrable experience of being a thought partner for Product and the Business
  • Natural collaborative leader and communicator who builds great relationships, making and brokering effective decisions at pace
  • A delivery‑excellence focused leader, who thrives on creating impact for our customers
  • Well versed in data engineering craft and technology
  • Proficient in the delivery and programme management of engineering teams
  • Strong influencer of senior stakeholders and business strategy
  • Strong commercial acumen

Benefits & Perks

  • A great, brand new office in the heart of Manchester
  • Free breakfast and lunch
  • 25 days’ paid holiday plus bank holidays (rising to 28 days after 3 years of service)
  • Health & well‑being benefits such as mental health support, access to health insurance, etc.
  • Employer contribution pension
  • Industry‑leading parental leave and adoption leave
  • Great discounts on accommodation, car rentals and other group benefits
  • From day one of your employment with us, we offer 22 weeks’ fully paid leave for all new parents, regardless of gender or the way you become a parent
  • Carer’s leave: 10 days’ fully paid leave per year for colleagues who are caring for ill family members
  • Hybrid Working (UK): We believe in office attendance at least 40% of your time whilst empowering you with the flexibility to plan where to do your best work

Inclusion at Booking.com

Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just create a unique workplace, it also creates a better, more inclusive travel experience for everyone. Inclusion is at the heart of everything we do. It’s a place where you can make your mark and have a real impact in travel and tech.”


Booking.com is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive.


#J-18808-Ljbffr

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 Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

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.