Lead Data Engineer (Data Infrastructure)

TN United Kingdom
London
1 month ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead data Engineer - Financial Markets - Day rate

Lead/Senior Data Engineer

Lead Data Engineer, Data Reliability

Lead Data Engineer

Social network you want to login/join with:

Client:

Motorway

Location:

London, United Kingdom

EU work permit required:

Yes

Job Reference:Job Views:

15

Posted:

14.03.2025

Expiry Date:

28.04.2025

Job Description:

Motorway is the UK’s fastest-growing used car marketplace – our award-winning, online-only platform connects private car sellers with thousands of verified dealers nationwide, ensuring everyone gets the best deal. Founded in 2017, our technology-led approach has redefined the experience of selling a car, generating thousands of monthly car sales and helping us to grow to a team of more than 400 people across our London and Brighton offices.

About the role

Our Data Engineering team is looking for a Lead Data Engineer to join them!

As our first Data Engineer, you'll play a pivotal role in bridging engineering best practices with our data domain. Our team is committed to transforming data into actionable insights, aiding decision-making processes and enhancing our products.Your expertise will drive advancements in our data engineering practices, leading the development of new data products with a focus on data backends, infrastructure, and DataOps.

If you thrive on enhancing infrastructure scalability, and designing sophisticated data architectures, then this role is perfect for you!

During your first 12 months, you will:

  • Build and Launch our new event-driven data operational architecture.
  • Successfully enhance the reliability and scalability of the data platform infrastructure.
  • Strengthen the data privacy and data retention foundations, ensuring compliance with the latest regulations.
  • Achieve measurable improvements in platform cost efficiency and scalability.

What you'll do

  • Design Data Architecture: Spearhead the development of an event-driven operational data architecture.
  • Optimise Infrastructure: Ensure the scalability and reliability of our data pipelines and infrastructure.
  • Advance Data Privacy: Strengthen our data privacy and retention frameworks, ensuring compliance and security.
  • Platform Optimisation: Streamline our data platform for enhanced cost efficiency and scalability.

Requirements

  • Proven experience with cloud data infrastructure on GCP or AWS, preferably GCP.
  • Expertise in event-driven data integrations and click-stream ingestion.
  • Proven ability in stakeholder management and project leadership.
  • Proficiency in SQL, Python, PySpark.
  • Solid background in data pipeline orchestration, data access, and retention tooling.
  • Demonstrable impact on infrastructure scalability and data privacy initiatives.
  • A collaborative spirit, innovative problem-solving skills, and excellent communication abilities.

Benefits

  • Annual learning budget - with your learning budget, you can pay for learning experiences to support your progression.
  • BUPA health insurance.
  • Discounted dental through BUPA.
  • Discounted gym membership through BUPA.
  • OnHand volunteering membership and one paid volunteering day per year.
  • Hybrid working from home (approximately 1-2 days in the office a week).
  • Motorway car leasing scheme - lease a zero-emissions electric vehicle at a significant discount.
  • Enhanced parental leave - We offer enhanced maternity pay (26 weeks of full pay) and enhanced paternity pay (4 weeks of full pay) to eligible employees.
  • Top spec MacBook Pro and peripherals.
  • Cycle to work scheme.

Equal opportunities statement

We are committed to equality of opportunity for all employees. We work to provide a supportive and inclusive environment where people can maximise their full potential. We believe our workforce should reflect a variety of backgrounds, talents, perspectives and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing and advancing individuals based on their skills and talents.

We welcome applications from all individuals regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships.

#J-18808-Ljbffr

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.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.