At a Glance
- Tasks: Design and build data pipelines for real-time analytics in a fast-growing digital platform.
- Company: Join a rapidly scaling UK-based consumer platform focused on data-driven growth.
- Benefits: Competitive salary, remote work, and clear progression opportunities.
- Other info: Work with cutting-edge tools and tackle complex data challenges at scale.
- Why this job: Make a real impact on a modern data platform and engineering culture.
- Qualifications: Strong experience in data engineering with advanced Python and SQL skills.
The predicted salary is between 90000 - 100000 € per year.
This is an opportunity to join a fast scaling, digital first consumer platform at a pivotal point in its data journey. They are investing heavily in their data infrastructure and are building a high performing, software led data engineering team to support real time, high volume analytics across the business. You will have genuine influence over how data engineering is done, working on modern tooling and best practice from day one.
The Company
They are a UK based, consumer facing digital platform operating in a highly regulated online environment. Since launching less than a decade ago, the business has grown rapidly, supported by significant recent funding and a strong focus on product, user experience and responsible engagement. Data is central to their growth strategy, and they are building a modern, scalable analytics platform to support this ambition. The team operates fully remotely across the UK and Europe.
The Role
- Design, build and own end to end data pipelines supporting real time and batch analytics
- Work on high volume, low latency data use cases with a strong focus on reliability and scalability
- Develop production grade data solutions using software engineering best practices such as CI/CD, testing and version control
- Contribute to the design of data models and analytics layers used across the business
- Help implement and mature staging, testing and deployment processes across the data platform
- Collaborate closely with analytics, product and engineering teams to enable better decision making
Your Skills and Experience
- Strong commercial experience as a data engineer in modern, cloud based environments
- Advanced Python and SQL, with experience using PySpark or similar distributed processing frameworks
- Experience building and maintaining data pipelines in AWS using services such as S3, Glue or EKS
- Hands on experience with modern analytics stacks such as Snowflake, dbt and Iceberg
- Familiarity with orchestration tools such as Dagster or Airflow
- Strong understanding of data modelling concepts and analytics best practice
- A software engineering mindset, including Git, testing and CI/CD workflows
What They Offer
- The chance to help shape a growing data platform and engineering culture
- Clear progression opportunities as the data team continues to expand
- Exposure to complex, real world data challenges at scale
How to Apply
If you are a Senior Data Engineer looking to make a real impact in a growing, product led business, apply now to learn more about the opportunity.
(111) Senior Data Engineer employer: LinkedIn
Join a dynamic and rapidly growing digital platform that places data at the heart of its strategy, offering you the chance to shape a cutting-edge data engineering culture. With a fully remote work environment across the UK and Europe, you'll enjoy a flexible work-life balance, alongside clear progression opportunities as the team expands. This role not only allows you to tackle complex data challenges but also empowers you to influence best practices from day one, making it an exciting opportunity for meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land (111) Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups or webinars, and connect with current employees at the company. A personal touch can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving AWS, Python, and SQL. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding data modelling concepts. Practice common data engineering problems and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace (111) Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your commercial experience as a data engineer, especially with cloud-based environments and tools like AWS, Python, and SQL.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to our growing data platform. Mention specific projects or experiences that align with the role's requirements.
Showcase Your Technical Skills:Don’t forget to include any relevant technical skills, especially those related to data pipelines, analytics stacks, and orchestration tools. We want to see your hands-on experience with modern technologies!
Apply Through Our Website:For the best chance of success, make sure to apply through our website. This way, we can easily track your application and get back to you quickly. We’re excited to see what you bring to the table!
How to prepare for a job interview at LinkedIn
✨Know Your Data Tools
Make sure you’re well-versed in the tools mentioned in the job description, like AWS, Snowflake, and PySpark. Brush up on your knowledge of data pipelines and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data challenges. Think about situations where you had to ensure reliability and scalability in your data solutions, and be ready to explain your thought process.
✨Understand the Company’s Data Vision
Research the company’s growth strategy and how data plays a role in it. Be prepared to discuss how you can contribute to their data journey and what best practices you would implement to enhance their analytics platform.
✨Collaborate and Communicate
Since the role involves working closely with various teams, practice articulating your ideas clearly. Be ready to discuss how you’ve collaborated with product and engineering teams in the past to drive better decision-making through data.
