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 career growth potential and the chance to make a real impact.
- Why this job: Join a dynamic team and shape the future of data architecture.
- Qualifications: 5+ years in data engineering, strong Python and SQL skills required.
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
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.
Ingegnere Dati employer: SearchWorks
Join a dynamic and innovative technology company that is at the forefront of transforming industries through artificial intelligence and modern data infrastructure. As a fully remote Data Engineer, you will enjoy flexible working arrangements, competitive compensation, and the chance to make a significant impact on our AI-powered products. With a strong focus on employee growth and collaboration across teams, this role offers meaningful ownership and the opportunity to shape the future of data architecture in a fast-paced environment.
StudySmarter Expert Advice🤫
We think this is how you could land Ingegnere Dati
✨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 make it easy for you to find roles that match your skills and interests. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Ingegnere Dati
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, and don’t forget to mention any hands-on work with transformation frameworks like dbt or Spark.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you’re passionate about data engineering and how your background aligns with our mission of transforming industries through AI. Keep it engaging and personal!
Showcase Your Projects:If you've worked on relevant projects, whether in a professional setting or as personal endeavours, make sure to include them. We love seeing practical examples of your work, especially those involving data pipelines and cloud data warehouses.
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’re considered for the role. Plus, it shows us you’re keen on joining 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 like dbt or Spark. Be ready to discuss how you've applied these in real-world scenarios, as this will show your hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in previous roles, particularly around data quality and monitoring. Highlight how you identified issues and the steps you took to resolve them, demonstrating your proactive approach.
✨Familiarise Yourself with Their Tech Stack
Research the cloud data warehouses mentioned in the job description, such as Snowflake or BigQuery. If you have experience with these tools, be ready to discuss how you've used them to optimise performance and manage costs.
✨Collaborate and Communicate
Since the role involves working closely with product, engineering, and AI teams, think about how you've successfully collaborated in the past. Prepare to discuss your communication style and how you ensure alignment across different teams.
