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 solutions.
- Benefits: Fully remote work, competitive salary, flexible arrangements, and equity opportunities.
- Other info: Great career growth potential and a chance to make a real impact.
- Why this job: Join a dynamic team to shape the future of data architecture and AI-driven products.
- Qualifications: 5+ years in data engineering, strong Python and SQL skills, and cloud experience.
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.
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 & BI Engineer employer: SearchWorks
Our client is an exceptional employer, offering a fully remote work environment that promotes flexibility and work-life balance. With competitive salaries and potential equity participation, employees are rewarded for their contributions while enjoying opportunities for rapid growth in a fast-paced, innovative setting. The collaborative culture fosters meaningful impact, allowing Data Engineers to take ownership of their projects and influence the evolution of data architecture within a transformative technology landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Data & BI Engineer
✨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 projects, especially those involving Python, SQL, or any transformation frameworks you've used. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your past projects and how you tackled challenges, especially around data pipelines and quality checks.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data & BI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, SQL, and any transformation frameworks you've used. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include specific projects that demonstrate your data engineering skills. Whether it's building data pipelines or optimising warehouse costs, we love seeing real examples of your work and the impact it had.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your experience and skills. We appreciate a well-structured application!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at SearchWorks
✨Know Your Data Inside Out
Make sure you’re well-versed in the data engineering concepts mentioned in the job description. Brush up on your Python and SQL skills, and be ready to discuss your experience with transformation frameworks like dbt or Spark. Having specific examples of how you've built and optimised data pipelines will really impress them.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced in previous roles, especially around data quality and monitoring. Think of a couple of scenarios where you identified issues proactively and how you resolved them. This will demonstrate your hands-on experience and ability to improve workflows.
✨Collaborate Like a Pro
Since this role involves working closely with product, engineering, and AI teams, be ready to discuss your collaborative experiences. Share examples of how you’ve partnered with other teams to align operational and analytical systems. Highlighting your teamwork skills can set you apart from other candidates.
✨Stay Current with Emerging Technologies
Familiarise yourself with the latest trends in data engineering and AI-assisted development tools. Be prepared to discuss how you’ve adapted to new technologies in your past roles. Showing that you’re proactive about learning and evolving with the industry will resonate well with the interviewers.
