Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer - Mid Level

The Lead Agency
Liverpool
1 month ago
Create job alert
Overview

At TLA, we're proud to be consumer champions in the automotive space. We're constantly exploring smarter ways to connect people with the right cars — and that's where data engineering plays a key role.


You'll join a focused data team of 4 professionals (2 Data Scientists, 1 BI Developer, and yourself as Data Engineer), working collaboratively to deliver high-impact data solutions. As part of the team, you'll create data pipelines to extract diverse datasets from vehicle stock volumes to customer reviews and offers data in a timely, robust and efficient manner. We understand that great data forms the backbone of great data analysis, and as such the data engineer is crucial to the success of the data department overall.


TLA works with the modern data stack, utilising Snowflake for our data warehouse, dbt to transform data across our medallion architecture, and Apache Airflow for orchestration. Microsoft Azure is our choice of cloud provider for hosting infrastructure. Within the role you will be hands-on with all these exciting technologies.


Many datasets you extract will require web scraping, it’s important that you have some experience within this domain.


What You'll Be Doing


What You'll Be Doing

You'll play a key role in optimising our data assets by:



  • Building and refining data ingestion pipelines for new data assets including vehicle stock data, offers and pricing data, images and more.
  • Developing analytics-focused data models in dbt to supply analysts and data scientists with clean, well-structured datasets.
  • Implementing and maintaining CI/CD pipelines for our data infrastructure, ensuring automated testing and smooth deployments.
  • Participating in code reviews and contributing to team standards for data pipeline development.
  • Keeping on top of the latest datasets available within the automotive space and making recommendations about new data sources.
  • Supporting and expanding our Microsoft Azure infrastructure, optimising it for data pipeline performance.
  • Writing comprehensive data documentation for analytics-focused entities, accelerating your colleagues' understanding of available data.

What You'll Need to Succeed

Essential Requirements:



  • 2-4 years of experience building robust data pipelines in a commercial environment or through complex personal projects.
  • Strong Python skills including experience with web scraping libraries (scrapy, requests, selenium etc.) and writing production-ready, testable code.
  • Advanced SQL skills with experience in query optimisation and data modelling.
  • Solid understanding of software engineering principles (SOLID, DRY, design patterns) applied to data engineering.
  • Experience with version control (Git) and collaborative development workflows.
  • Understanding of CI/CD concepts and experience contributing to automated testing strategies.
  • Knowledge of data quality principles including data validation, monitoring, and automated testing frameworks
  • Understanding of a framework for modern ELT workflows i.e., dbt, sql-mesh etc.
  • Experience working with a cloud platform i.e., AWS, Azure, GCP etc.
  • Must be located within a 1-hour commute to Liverpool city centre (non-negotiable due to regular in-office collaboration requirements)

Nice-to-Have Skills:



  • Experience with both batch and near real-time data pipelines
  • Familiarity with Infrastructure as Code (Terraform)
  • Experience with dbt and medallion architecture patterns
  • Knowledge of Apache Airflow or similar orchestration tools
  • Azure cloud platform experience

Why Join TLA?

TLA is a fast-moving, innovative digital business that partners with some of the biggest automotive brands—including the Volkswagen Group, BMW Group, and Ford. Founded over 20 years ago, and with long-standing team members, we've built a close-knit, ambitious team that's passionate about pioneering technology to drive car sales.


We offer a supportive and collaborative environment, where you'll have the opportunity to grow and make an impact. Our hybrid model (2 days per week in our fantastic Liverpool city centre office) enables in-office teamwork and collaboration. We're a highly driven bunch that believes in respect, hard work, and giving back through charitable events and sporting efforts—everything from hiking to skydiving!


PLEASE NOTE: This role is only open to those with the right to work in the UK without the need for sponsorship or visa, now or in the future.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.