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- Tasks: Build and maintain scalable data pipelines and support real-time data workflows.
- Company: Fast-growing entertainment company with a strong data culture.
- Benefits: Hybrid working, flexible hours, and opportunities for career growth.
- Other info: Collaborate with talented peers and work with modern tech tools.
- Why this job: Make a tangible impact in a creative environment while deepening your technical expertise.
- Qualifications: 2-3 years in data engineering, strong SQL skills, and programming knowledge.
The predicted salary is between 45000 - 55000 £ per year.
A fast-growing entertainment company is expanding its data engineering team to build a modern, scalable data foundation that powers analytics, experimentation, and machine learning across the business. Data plays a key role in how the company grows, innovates, and delivers great experiences for its users. You’ll work alongside experienced engineers and data scientists to shape and evolve the platform that underpins all data-driven decisions — including the development of real-time streaming capabilities using tools like Kafka.
This is a great opportunity for someone with early career experience in data engineering who’s ready to deepen their technical expertise and make a tangible impact in a creative, fast-paced environment.
Key Responsibilities:- Build and maintain reliable, scalable data pipelines for structured, semi-structured, and streaming data
- Design and improve data models to support analytics and machine learning use cases
- Develop and support real-time data workflows using technologies such as Apache Kafka
- Monitor and ensure data quality, reliability, and security across the stack
- Contribute to the evolution of data engineering practices, tooling, and automation
- Collaborate with analytics, product, and data science teams to make data accessible and trustworthy
- 2–3 years of experience in data engineering or a similar role
- Strong SQL skills and proficiency in at least one programming language (ideally Python)
- Understanding of data warehousing concepts and ETL/ELT patterns
- Experience with version control (Git), testing, and code review practices
- Familiarity with cloud-based data environments (e.g. AWS, GCP, or Azure)
- Exposure to modern data tools such as Airflow, dbt, or Snowflake
- Experience or strong interest in streaming technologies like Apache Kafka
- Interest in MLOps and modern data engineering best practices
You’ll be part of a company with a clear mission and strong data culture, joining a team that values learning, collaboration, and creativity. The role offers real opportunities to grow towards senior and platform-focused positions, working with a modern tech stack and talented peers.
Package & Setup:- 3 days per week in the central London office
- Hybrid and flexible working
Data Engineer employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the data engineering field on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, or real-time data workflows. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and programming skills. We recommend practicing common data engineering problems and being ready to discuss your past experiences with data pipelines and tools like Kafka.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your SQL skills, programming experience, and any relevant projects you've worked on. We want to see how you can contribute to our data engineering team!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for data engineering. Share why you're excited about this role and how your background aligns with our mission. Keep it concise but engaging!
Showcase Your Projects: If you've worked on any data pipelines, models, or real-time workflows, make sure to mention them! We love seeing practical examples of your work, especially if they involve tools like Kafka or cloud environments. It helps us understand your hands-on experience.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our team at StudySmarter!
How to prepare for a job interview at Xcede
✨Know Your Data Tools
Make sure you brush up on your knowledge of data tools mentioned in the job description, like Apache Kafka and SQL. Be ready to discuss how you've used these tools in past projects or how you would approach using them in this new role.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in data engineering and how you solved them. This could involve discussing a data pipeline you built or a complex ETL process you optimised. Real-world examples will help demonstrate your expertise.
✨Understand the Company’s Data Culture
Research the company’s mission and how they leverage data to enhance user experiences. Being able to articulate how your values align with theirs and how you can contribute to their data-driven decisions will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the tech stack, and future projects. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you. Plus, it gives you a chance to engage with your interviewers!