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

Apply Now

Senior Data Engineer

CreateFuture
City of London
2 weeks ago
Create job alert
Who we are

CreateFuture is fast becoming the UK's most recognisable digital consultancy, with years of experience building digital products and services for major organisations whilst putting our people first. We have offices in the centre of Edinburgh, Leeds, Manchester, and London as well as remote employees located throughout the country.

We are a team of creators - whether that's code, project plans, go to market strategies, culture initiatives, marketing campaigns, large language models or people policies. And together, with our clients, we create the future. This has seen us collaborate and partner across a multitude of industries and sectors, with the likes of PayPal, adidas, Natwest, FanDuel and Money Saving Expert, to name just a few.

Our reputation as a partner determined to deliver high-quality, robust and thoughtful products has enabled us to scale to over 500 people in the last couple of years, and it is our amazing people - along with the safe, supportive and friendly culture we have built - that makes CreateFuture a great place to work. Don\'t just take our word for it though, we have been recognised by Best Workplaces UK multiple years in a row - across a number of categories - and our employee exit rate is astonishingly low.

Join us on our journey... Let\'s create something awesome, together, today.

About the role and team

We\'re looking for a Data Engineer to join our growing Data Practice. You\'ll work as part of a multidisciplinary team delivering data solutions for some of the UK\'s best-known brands. You\'ll have a hand in everything from data ingestion and transformation to pipeline automation and data platform optimisation - always with a strong focus on quality, scalability, and value.

What you\'ll be doing
  • Designing, building and maintaining robust, cloud-native data pipelines
  • Automating and orchestrating workflows using tools like AWS Glue, Azure Data Factory, or Google Cloud Dataflow
  • Working with platform services such as Amazon S3, Azure Synapse, Google BigQuery, and Snowflake
  • Implementing Lakehouse architectures using tools like Databricks or Snowflake
  • Collaborating closely with engineers, analysts, and client teams to deliver value-focused data solutions
We\'d love to talk to you if
  • You\'ve got solid experience working with Python, SQL, Spar and data pipeline tools such as dbt or Airflow
  • You\'re comfortable working across cloud platforms - especially AWS (Glue, Lambda, Athena), Azure (Data Factory, Synapse), or GCP (Dataflow, BigQuery, Cloud Composer)
  • You have a good understanding of data modelling, data warehousing and performance optimisation
  • You care deeply about data quality, testing, and documentation
  • You enjoy solving real-world problems and collaborating with cross-functional teams
  • You\'re comfortable in a consultancy setting, balancing hands-on delivery with client engagement
What we\'ll offer you

At CreateFuture, we challenge ourselves to go beyond the obvious and we care deeply about our craft and customers. With us, you\'ll have ambitious projects to sink your teeth into and plenty of opportunities to learn and grow. You\'ll be part of our safe, supportive and friendly culture - that looks after you - and join our team of genuinely great people.

Our benefits include:

  • Total 35 days holiday (we have flexible bank holidays)
  • Comprehensive private medical insurance
  • Enhanced parental and adoption leave
  • Pension - matched up to 5%

View our complete list of benefits here.

As this is a hybrid role, we\'re looking for people within a commuting distance of our hub locations (Edinburgh/Leeds/Manchester/London) and who are flexible to travel to client sites and CreateFuture regional offices. We are very flexible and trust you to manage your own schedule to balance face-to-face time with clients, colleagues and working from home.

We create and reinforce a culture that rewards employees' impact, not just activity. We trust our employees to work autonomously and promote ownership across all levels.

Next steps

Our Talent team aims to respond to all applications within a reasonable timeframe, regardless of whether or not we progress your application.

Our interview process:

  • 30-minute call with one of our Talent Acquisition Team.
  • 1-hour competency-based interview
  • Take Home Task & Review
  • 60-minute values-led interview.

Our interview process is designed as an opportunity both for our interviewers to learn about your expertise, interests and motivations and for you to gain insights into the role, team and business as a whole, so throughout the process, you\'ll meet a few people from our team as well as others from across the business to help you get a well-rounded view of the role and life at CreateFuture.

We believe that representative teams made up of people with different backgrounds, skills, and points of view help us build the best workplace possible, and enable us to create genuinely innovative, broadly useful products.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior 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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.