Data Engineer

FanDuel
Edinburgh
4 months ago
Create job alert
Data Engineer

We are looking for a Data Engineer to join our growing data engineering team and help build the pipelines and infrastructure that power analytics, machine learning, and business decision‑making across the company. In this role, you’ll contribute to the design, development, and maintenance of reliable data systems while collaborating with stakeholders to support high‑impact data use cases.


Responsibilities

  • Design, build, and maintain scalable batch and streaming data pipelines to support analytics and business operations.
  • Write clean, efficient, and well‑documented code using tools like Python, SQL, and Spark.
  • Ensure data is reliable, accurate, and delivered in a timely manner.
  • Work with data analysts, data scientists, and product managers to understand requirements and deliver actionable data solutions.
  • Translate business questions into engineering tasks and contribute to technical planning.
  • Participate in code reviews, sprint planning, and retrospectives as part of an agile team.
  • Monitor data pipelines and troubleshoot issues in a timely, systematic manner.
  • Implement data quality checks and contribute to observability and testing practices.
  • Document data sources, transformations, and architecture decisions to support long‑term maintainability.

Qualifications

  • Experience in data engineering, analytics engineering, or software engineering with a focus on data.
  • Strong SQL skills and familiarity with at least one programming language (e.g., Python, Java, or Scala).
  • Hands‑on experience with modern data tools such as Databricks, Airflow, DBT, Spark, or Kafka.
  • Understanding of data modeling concepts, data warehousing, and ETL/ELT best practices.
  • Experience working with cloud‑based data platforms (AWS, GCP, or Azure).

Preferred Qualifications

  • Experience supporting BI, analytics, or data science teams.
  • Familiarity with version control, CI/CD, and collaborative development workflows.
  • Exposure to data governance, privacy, or compliance practices.
  • Eagerness to learn new technologies and contribute to the growth of the team.

Benefits

  • An exciting and fun environment committed to driving real growth.
  • Opportunities to build really cool products that fans love.
  • Career and professional development resources to help you refine your game plan for owning and driving your career and development.
  • Be well, save well and live well – with FanDuel Total Rewards your benefits are one highlight reel after another.

Diversity, Equity and Inclusion

FanDuel is an equal opportunities employer. Diversity and inclusion in FanDuel means that we respect and value everyone as individuals. We don't tolerate bias, judgement or harassment. Our focus is on developing employees so that they reach their full potential.


FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email .


The requirements listed in our job descriptions are guidelines, not hard and fast rules. You don't have to satisfy every requirement or meet every qualification listed. If your skills are transferable and you are in the ballpark experience‑wise, we'd love to speak to you!


Location: Edinburgh, Scotland, United Kingdom


#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.

New Data Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly. For professionals exploring opportunities on www.DataEngineeringJobs.co.uk , the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

What Hiring Managers Look for First in Data Engineering Job Applications (UK Guide)

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.