Senior Data Engineer

ADLIB Recruitment | B Corp
Bristol
3 weeks ago
Create job alert

FTSE100 Company

  • Join a small, collaborative team with big impact.
  • Bring ideas to life using modern tech like Databricks and AWS.
  • Flexible hybrid working and strong support from leadership.


We’re working with a well-established organisation that’s on an exciting journey to bring more of their data capability in-house — and this is a rare chance to get in at the start of something transformative.


What You'll be Doing:

As the new Senior Data Engineer, you’ll play a key role in building modern, scalable pipelines and platforms that will enable the business to make smarter decisions, faster. You’ll be part of a small but highly capable core data engineering team, within a wider, strong data & insight function. This is a role for someone who’s curious, proactive, and keen to get stuck in — you’ll have plenty of ownership, and your voice will absolutely be heard.


Working closely with the Data Engineering Lead, you’ll help design, build and maintain cloud-based data pipelines and architecture. The business is moving towards a tight-knit, fully internal team — so you’ll be a big part of shaping that change.


You’ll lead by example when it comes to data engineering and problem-solving. This would mean improving existing pipelines, building new ones from scratch, helping shape best practices, mentoring more junior engineers, or exploring the latest tools and tech.


The team are using Databricks and AWS and they’re keen for someone who’s worked across data warehouse architecture, orchestration tools like Airflow, and configuration-driven development. You’ll also work closely with analysts, scientists and other business teams, so you’ll need to be able to explain complex technical concepts in a clear, concise way and comfortable working in a crss functional team.


What experience you’ll need to apply:

  • Excellent experience as a Senior Data Engineer, with some experience mentoring others
  • Excellent Python and SQL skills, with hands-on experience building pipelines in Spark (PySpark preferred)
  • Experience with cloud platforms (AWS/Azure)
  • Solid understanding of data architecture, modelling, and ETL/ELT pipelines
  • Experience using tools like Databricks, Redshift, Snowflake, or similar
  • Comfortable working with APIs, CLIs, and orchestration tools like Airflow
  • Confident using Git and familiar with CI/CD processes (Azure DevOps or similar)
  • Experience working in an Agile environment
  • A proactive mindset — you ask questions, think critically, and enjoy working things out collaboratively


What you’ll get in return:

A salary of between £60,000–£65,000 per annum, within a hybrid working environment (ideally 3 days in their Bristol office), plus a discretionary bonus and strong pension.


What’s next?

Apply with your updated CV, and we’ll review your application as soon as possible to set up a call and chat through the role in more detail! If you’ve got any questions in the meantime, feel free to drop Tegan an email.

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - Databricks

Senior Data Engineer - DV Cleared

Senior Data Engineer - MS Fabric - Remote - £70k - £75k

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.

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.