At a Glance
- Tasks: Design and build data pipelines, ensuring smooth data flow and quality.
- Company: Fast-growing tech company revolutionising industries with AI and modern data infrastructure.
- Benefits: Flexible working, competitive salary, equity options, and rapid growth opportunities.
- Other info: Fully remote role with meaningful ownership and influence on projects.
- Why this job: Join a dynamic team and shape the future of data architecture in an innovative environment.
- Qualifications: 5+ years in data engineering, strong Python and SQL skills, experience with Spark.
The predicted salary is between 80000 - 120000 £ per year.
Our client is a fast-growing, venture-backed technology company transforming a large, complex industry through artificial intelligence and modern data infrastructure. We’re building AI-powered products that combine advanced automation with human expertise to improve operational workflows, reduce friction, and create better customer experiences at scale.
We’re looking for a Data Engineer to build and scale the data foundations that power our platform, customer experience, analytics, and AI systems.
Fully Remote - Salary Dependant on Experience (£80,000-£120,000)
As a Data Engineer, you'll design and operate the infrastructure that moves, transforms, and structures data across our systems. You'll work across ingestion pipelines, transformation layers, monitoring, customer onboarding, and analytics while partnering closely with product, engineering, and AI teams. This is a hands-on role with meaningful ownership and the opportunity to influence how data architecture evolves as the business scales.
- Design and build reliable end-to-end data pipelines connecting customer systems, internal platforms, and AI-generated outputs
- Create and maintain transformation layers that convert raw data into trusted, documented datasets
- Implement monitoring, alerting, and data quality checks to proactively identify issues
- Lead customer data onboarding by mapping datasets and building scalable integration processes
- Improve performance and optimize warehouse costs as data volumes grow
- Collaborate with backend, AI, and product teams to align operational and analytical systems
- Establish best practices for data modeling, testing, documentation, schema management, and code review
- Support and improve AI-driven workflows and data capabilities
Requirements:
- 5+ years of experience in data engineering within production environments
- Strong Python and SQL skills
- Hands-on experience with transformation frameworks such as dbt or Spark
- Experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Databricks
- Strong understanding of data modeling principles across analytical and operational systems
- Experience with monitoring and data quality tooling
- Familiarity with CI/CD practices and testing for data workflows
- Comfortable working with emerging technologies, including AI-assisted development tools
Flexible working arrangements, competitive compensation, and potential equity participation. Opportunities for rapid growth and meaningful impact.
Data Engineer Con Spark/Scala (Remoto) employer: SearchWorks
Join a dynamic and innovative technology company that is at the forefront of transforming industries through AI and modern data infrastructure. As a Data Engineer, you will enjoy a fully remote work environment with flexible arrangements, competitive compensation, and opportunities for rapid growth, all while making a meaningful impact on customer experiences and operational workflows. Our collaborative culture encourages ownership and creativity, allowing you to influence the evolution of our data architecture as we scale.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer Con Spark/Scala (Remoto)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Spark and Scala. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when designing data pipelines or optimising performance – it’s all about demonstrating your expertise!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Data Engineer Con Spark/Scala (Remoto)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data pipelines, transformation frameworks like Spark, and any relevant cloud data warehouse experience. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our mission of transforming industries with AI. Keep it concise but impactful – we love a good story!
Showcase Your Projects:If you've worked on any cool data projects, don’t forget to mention them! Whether it's building data pipelines or optimising data models, we want to see your hands-on experience. Include links to your GitHub or any relevant portfolios if you have them.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at SearchWorks
✨Know Your Data Engineering Stuff
Make sure you brush up on your data engineering skills, especially with Spark and Scala. Be ready to discuss your experience with data pipelines, transformation frameworks, and cloud data warehouses like Snowflake or BigQuery. They’ll want to see that you can not only talk the talk but also walk the walk!
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in previous roles. Think about times when you improved data quality or optimised performance. This is your chance to demonstrate your analytical thinking and how you can contribute to their AI-driven workflows.
✨Understand Their Business
Do a bit of homework on the company and its products. Understand how they use data to enhance customer experiences and operational workflows. This will help you tailor your answers and show that you're genuinely interested in how you can fit into their mission.
✨Ask Smart Questions
Prepare thoughtful questions to ask at the end of the interview. Inquire about their data architecture evolution or how they integrate AI into their systems. This shows that you’re engaged and thinking critically about the role and its impact on the company.
