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 data infrastructure.
- Benefits: Fully remote work, competitive salary, flexible arrangements, and equity opportunities.
- Other info: Great potential for rapid growth and making a real impact.
- Why this job: Join a dynamic team and shape the future of data architecture in a thriving environment.
- 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.
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
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.
Senior Engineer, Data Engineering employer: SearchWorks
As a fast-growing technology company, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to innovate and excel. With fully remote working options, competitive salaries, and opportunities for rapid growth, we offer a unique environment where your contributions directly influence the evolution of our AI-powered products. Join us to be part of a team that values collaboration, creativity, and meaningful impact in transforming a complex industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer, Data Engineering
✨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 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 common data engineering questions and scenarios. Practice explaining your thought process and how you've tackled challenges in past roles—this will help you shine during those crucial conversations.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Data Engineer role. Highlight your Python, SQL, and cloud data warehouse experience to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to our mission. Share specific examples of your past work that relate to the job description.
Showcase Your Projects:If you've worked on any relevant projects, whether personal or professional, make sure to mention them. We love seeing hands-on experience, especially with data pipelines and transformation frameworks like dbt or Spark.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and get back to you quickly!
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 tackled real-world data challenges in production environments.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've designed and built data pipelines or improved data quality. Think about times when you had to troubleshoot issues or optimise performance, and be ready to explain your thought process.
✨Understand the Company’s Tech Stack
Familiarise yourself with the cloud data warehouses mentioned in the job description, such as Snowflake or BigQuery. Knowing how these tools fit into the company's operations will show that you're genuinely interested and can hit the ground running.
✨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 communication skills and any experience you have with CI/CD practices, as this will demonstrate your ability to work effectively in a team environment.
