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: Fully remote work, competitive salary, flexible arrangements, and equity participation.
- Other info: Opportunities for rapid growth and meaningful impact in an innovative environment.
- Why this job: Join a dynamic team and shape the future of data architecture in a rapidly scaling business.
- Qualifications: 5+ years in data engineering, strong Python and SQL skills, and experience with cloud data warehouses.
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.
Bi Data Engineer employer: SearchWorks
Join a fast-growing, venture-backed technology company that is at the forefront of transforming a complex industry through innovative AI solutions. 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 our data architecture and customer experience. Our collaborative culture fosters creativity and expertise, ensuring you have the support and resources needed to thrive in your role.
StudySmarter Expert Advice🤫
We think this is how you could land Bi Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with current employees at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your data engineering projects. 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 your technical skills and understanding the company’s products. Be ready to discuss how your experience aligns with their needs, especially around data pipelines and AI systems.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Engineers, and applying directly can give you an edge. Plus, it shows you’re genuinely interested in joining our team!
We think you need these skills to ace Bi Data 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 like dbt or Spark. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include specific projects where you've designed and operated data pipelines or worked with cloud data warehouses. This gives us a clear picture of your hands-on experience and how you can contribute to our team.
Be Clear and Concise:When writing your cover letter, keep it clear and to the point. Explain why you're excited about the role and how your background makes you a great fit. We appreciate straightforward communication!
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 Engineering Stuff
Make sure you brush up on your data engineering skills, especially in Python and SQL. Be ready to discuss your hands-on experience with transformation frameworks like dbt or Spark, and how you've used cloud data warehouses such as Snowflake or BigQuery in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in data pipelines or data quality issues. Think about times when you implemented monitoring or alerting systems to proactively identify problems and how that improved the overall workflow.
✨Collaborate Like a Pro
Since this role involves working closely with product, engineering, and AI teams, be ready to discuss your experience in cross-functional collaboration. Highlight any projects where you aligned operational and analytical systems, and how you established best practices for data modelling and documentation.
✨Be Ready for Technical Questions
Expect some technical questions during the interview. Brush up on data modelling principles and CI/CD practices for data workflows. You might also want to think about how emerging technologies, including AI-assisted tools, can enhance data engineering processes.
