At a Glance
- Tasks: Design and build data pipelines, transform data, and create analytics solutions.
- 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 a collaborative and innovative culture.
- Why this job: Join a dynamic team and make a real impact in the AI space.
- Qualifications: 5+ years in data engineering, strong Python and SQL skills required.
The predicted salary is between 80000 - 125000 £ 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. As an early-stage team, we’re focused on solving meaningful challenges using modern technology and creating a culture where ownership, innovation, and impact matter.
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.
Responsibilities:- 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
- Develop dashboards and analytics solutions for both internal teams and customer-facing insights
- 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
- 5+ years of experience in data engineering within production environments
- Strong Python and SQL skills
- Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or similar
- 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
- Modern tools and equipment
- Opportunities for rapid growth and meaningful impact
- Collaborative and highly talented team environment
Data Engineer employer: SearchWorks
As a fast-growing technology company, we pride ourselves on fostering a culture of innovation and ownership, where every team member has the opportunity to make a significant impact. With fully remote working options, competitive compensation, and a focus on employee growth, we provide a collaborative environment that empowers our Data Engineers to thrive while tackling meaningful challenges in the AI space.
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 industry, attend virtual meetups, and connect with fellow data enthusiasts 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 projects, whether it's a GitHub repo or a personal website. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and practical tasks. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Engineers. Plus, it’s a great way to ensure your application gets the attention it deserves.
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 Python, SQL, and data engineering experience to show us you’re the right fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about this opportunity. Share specific examples of how you've tackled challenges in data engineering and how you can contribute to our mission.
Showcase Your Projects:If you've worked on any relevant projects, don’t hesitate to include them! We love seeing real-world applications of your skills, especially those involving data pipelines and analytics solutions.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at SearchWorks
✨Know Your Data Engineering Fundamentals
Brush up on your data engineering principles, especially around data pipelines and transformation frameworks. Be ready to discuss your experience with tools like Python, SQL, and workflow orchestration tools such as Airflow or Prefect. This will show that you understand the core responsibilities of the role.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in previous roles. Think about specific projects where you improved data quality or optimised performance. This will demonstrate your hands-on experience and ability to make an impact in a fast-paced environment.
✨Familiarise Yourself with Their Tech Stack
Research the technologies mentioned in the job description, like Snowflake, BigQuery, or Databricks. If you have experience with these tools, be ready to discuss it. If not, show your willingness to learn and adapt to new technologies, especially in AI-driven workflows.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data architecture and how they envision the role evolving. This shows your genuine interest in the position and helps you gauge if the company culture aligns with your values, especially around ownership and innovation.
