Head of Data Engineering & Architecture

Trainline
London
1 week ago
Create job alert

About us:We are champions of rail, inspired to build a greener, more sustainable future of travel. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through our highly rated mobile app, website, and B2B partner channels.Great journeys start with TrainlineNow Europe’s number 1 downloaded rail app, with over 125 million monthly visits and £5.3 billion in annual ticket sales, we collaborate with 270+ rail and coach companies in over 40 countries. We want to create a world where travel is as simple, seamless, and affordable as it should be.Today, we're a FTSE 250 company driven by our incredible team of over 1,000 Trainliners from 50+ nationalities, based across London, Paris, Barcelona, Milan, Edinburgh and Madrid. With our focus on growth in the UK and Europe, now is the perfect time to join us on this high-speed journey.Head of Data Engineering & Architecture

The full job description covers all associated skills, previous experience, and any qualifications that applicants are expected to have.London (Hybrid, 40% in office) £Salary + Bonus + Equity + BenefitsWe are recruiting for an experienced Head of Data Engineering & Architecture to build a world-class Data Engineering function and data platform, owning both strategy and delivery for Data Engineering as a discipline along with the vision, roadmap, operations and cost of the Data platform and associated products.As Head of Data Engineering and Architecture you will...Lead the organization of circa 30 Data Engineers and Data Engineering Managers.Set the vision and strategy for the Data Engineering function and drive necessary organisational change to achieve the vision.Set the vision, technology blueprint, architecture and roadmap of the Data Platform.Ensure delivery of OKRs for Data and vertical Data Product Teams.Architect our analytical data stores to maximise productivity and efficiency for data consumers with effective metrics and data marts.Ensure that our data assets are discoverable, documented and readily accessible to consumers and appropriately protected.Engage and nurture the Data Engineering teams to drive and foster a high engagement culture.Manage the costs of data systems and 3rd party suppliers within the current FY budget and accurately forecast the next FY budget.Define and implement effective ways of working for delivery teams and ensure these are embedded.Influence the direction of our technology platforms so that they are aligned to the needs of delivery teams and drive adoption of new technologies.Embed high standards of engineering excellence in delivery teams.Define effective operational processes and ensure that teams embed these processes and achieve operational performance targets for availability, performance, security, on-call rotas, incident management etc.Ensure the Data Engineering function engages with regulatory, audit or compliance teams and processes and achieves compliance with relevant policies in Data Governance, security, privacy and IT controls.Coordinate larger cross-team projects or programmes within the Data function and ensure that we have governance in place to manage delivery.We'd love to hear from you if you...Thrive in a diverse, open and collaborative environment.Have experience managing multiple teams of Data Engineers.Are an expert in data engineering infrastructure, technologies and practices.Have deep expertise in data modelling and warehouse design in the modern, lake house era.Are an experienced and committed people manager with technical leadership experience.Are passionate about agile software delivery with a track record of leading effective agile and lean software teams.Have a strong background in DevOps deploying, managing and maintaining services using Airflow, Docker, Terraform and AWS CLI tools to achieve infrastructure-as-code and automated deployments.Have excellent knowledge of AWS services (ECS, IAM, EC2, S3, DynamoDB, MSK).Our Technology StackPython and ScalaStarburst and AthenaKafka and KinesisDataHubML Flow and AirflowDocker and TerraformKafka, Spark, Kafka Streams and KSQLDBTAWS, S3, Iceberg, Parquet, Glue and EMR for our Data LakeElasticsearch and DynamoDBMore information:Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, extra festive time off, and excellent family-friendly benefits.We prioritise career growth with clear career paths, transparent pay bands, personal learning budgets, and regular learning days. Jump on board and supercharge your career from day one!Our values represent the things that matter most to us and what we live and breathe every day, in everything we do:Think Big

- We're building the future of railOwn It

- We focus on every customer, partner and journeyTravel Together

- We're one teamDo Good

- We make a positive impactInterested in finding out more about what it's like to work at Trainline? Why not check us out on LinkedIn, Instagram and Glassdoor!

#J-18808-Ljbffr

Related Jobs

View all jobs

Head of Data Engineering - Private Markets - London/Hybrid | London, UK

Head of Engineering

Head of Data and Analytics Engineering

Head of Data and Analytics Engineering

Head of Data and Analytics Engineering

Director, Data Architecture

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.