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 opportunities for rapid growth and making a real impact.
- 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, 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.
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 Architect employer: SearchWorks
As a fast-growing, venture-backed technology company, we offer an exceptional work environment that fosters innovation and collaboration. Our fully remote setup allows for flexible working arrangements, while our competitive compensation package and potential equity participation ensure that your contributions are recognised and rewarded. With ample opportunities for rapid growth and the chance to make a meaningful impact in transforming a complex industry through AI and data infrastructure, you'll find a fulfilling career with us.
StudySmarter Expert Advice🤫
We think this is how you could land BI / Data Architect
✨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. Whether it's a GitHub repo or a personal website, let your work speak for itself and demonstrate your expertise.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process and how you've tackled challenges in past roles—this will help you stand out!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight how your experience aligns with our mission and values.
We think you need these skills to ace BI / Data Architect
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, and any relevant projects that showcase your skills in Python and SQL. We want to see how you can bring value to our team!
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 your background aligns with our mission at StudySmarter. Be sure to mention any experience with AI-driven workflows or cloud data warehouses.
Showcase Your Projects:If you've worked on any interesting data projects, don’t hesitate to include them! Whether it's a personal project or something from your previous job, we love seeing practical examples of your skills in action. It helps us understand your hands-on experience better.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your materials in one go. Plus, it shows us you’re serious about joining the StudySmarter team!
How to prepare for a job interview at SearchWorks
✨Know Your Data Inside Out
Make sure you’re well-versed in the data engineering principles relevant to the role. Brush up on your Python and SQL skills, and be ready to discuss your experience with transformation frameworks like dbt or Spark. Being able to articulate how you've designed and operated data pipelines will definitely impress.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in previous roles and how you overcame them. Whether it’s about improving performance or optimising costs in data warehouses, having a few solid stories up your sleeve can really highlight your hands-on experience and critical thinking.
✨Familiarise Yourself with Their Tech Stack
Research the cloud data warehouses mentioned in the job description, like Snowflake or BigQuery. If you have experience with these tools, be ready to discuss how you’ve used them in past projects. This shows that you’re not just a fit for the role but also genuinely interested in their tech environment.
✨Collaborate and Communicate
Since this role involves working closely with product, engineering, and AI teams, be prepared to discuss how you’ve collaborated in the past. Highlight your ability to communicate complex data concepts to non-technical stakeholders, as this is key to ensuring everyone is on the same page.
