Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and maintain data pipelines for advanced analytics and AI-driven projects.
- Company: Join Quantios, a leader in enterprise data solutions with a collaborative culture.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make an impact by shaping the future of data engineering and analytics.
- Qualifications: 4+ years in data engineering with skills in Python, SQL, and cloud technologies.
- Other info: Dynamic team environment with a focus on continuous learning and innovation.
The predicted salary is between 36000 - 60000 £ per year.
As a Data Engineer at Quantios, you will play a critical role in building and maintaining the data foundation for Quantios Insights, our enterprise data platform that integrates data from all Quantios products and powers advanced analytics, MCP-based automation, and AI-driven use cases. You will design and operate robust data pipelines, ensure data quality and governance, and collaborate closely with developers, architects, and business stakeholders to deliver curated, reliable, and scalable datasets.
Job Responsibilities
- Data Pipeline Engineering
- Design, build, and maintain scalable ETL/ELT pipelines using Microsoft Fabric, Databricks, or Snowflake.
- Develop data ingestion processes for structured, semi-structured, and event-based data from Quantios products.
- Build scalable dataflows using Python, SQL, PySpark, or similar technologies.
- Implement automated data refresh, validation, and monitoring processes.
- Ensure pipelines are efficient, cost-effective, and aligned with enterprise data architecture standards.
- Data Modelling & Lakehouse Architecture
- Implement lakehouse/medallion architecture (bronze, silver, gold layers).
- Design and maintain semantic data models for analytics and AI-ready datasets.
- Optimize datasets for Power BI, Fabric semantic models, and other analytics tools.
- Collaborate with architects to maintain modelling standards and best practices.
- Data Quality & Governance
- Implement data validation, schema enforcement, and profiling to maintain high-quality datasets.
- Maintain data lineage using governance tools such as Fabric Data Governance, Databricks Unity Catalog, or Snowflake.
- Support metadata management and cataloguing tools such as Purview.
- Ensure compliance with data security, governance, and regulatory standards.
- AI & RAG Data Preparation
- Prepare structured and unstructured datasets for AI, RAG pipelines, and LLM evaluation.
- Collaborate with LLMOps engineers to provide high-quality training and validation datasets.
- Develop curated datasets for AI agents, semantic search, and internal experimentation.
- Support vectorisation workflows, chunking strategies, and semantic data preparation.
- Platform Delivery & Customer Enablement
- Support customer deployments of Quantios Insights across enterprise data platforms.
- Contribute to reference architectures and platform configuration guidelines.
- Work with Product Owners and Professional Services to streamline customer data onboarding.
- Assist customers in aligning their data environments with Quantios product structures.
- Collaboration & Agile Delivery
- Work closely with architects, product owners, and engineering teams to deliver data solutions.
- Translate analytical and AI requirements into scalable data engineering solutions.
- Participate in Agile ceremonies including backlog refinement, estimation, and sprint planning.
- Continuous Improvement
- Stay updated with emerging technologies in data engineering, analytics, and AI platforms.
- Identify opportunities to improve data reliability, performance, and automation.
- Contribute to internal best practices and promote high-quality engineering standards.
Job Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Data Science, or a related field; or equivalent industry experience.
- 4+ years of experience in data engineering, preferably within cloud-based or enterprise environments.
- Hands-on experience with one or more: Microsoft Fabric, Azure Databricks, Snowflake.
- Strong skills in Python and SQL, with exposure to PySpark or Spark SQL.
- Experience with Azure Data Lake Storage, Delta Lake, ELT/ETL pipelines, and medallion architecture.
- Familiarity with Power BI, Fabric semantic models, or equivalent BI modelling tools.
- Practical experience integrating with CI/CD tools, especially Azure DevOps.
- Understanding of data governance, cataloguing, and metadata management (e.g., Purview, Unity Catalog).
- Exposure to AI-related data preparation (RAG datasets, embeddings, unstructured text processing) is a plus.
- Excellent problem-solving skills, ability to work across teams, and strong communication skills.
Data Engineer (UK) in Fleet employer: Quantios
Contact Detail:
Quantios Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (UK) in Fleet
✨Tip Number 1
Network like a pro! Reach out to folks in the data engineering field on LinkedIn or at local meetups. 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 pipelines, models, and any cool projects you've worked on. 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 practical tests. Practice coding challenges in Python or SQL to keep your skills sharp and ready for anything they throw at you.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates. Plus, it shows you're genuinely interested in joining our team at Quantios.
We think you need these skills to ace Data Engineer (UK) in Fleet
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, ETL/ELT processes, and any relevant technologies like Microsoft Fabric or Databricks. We want to see how your skills match what we're looking for!
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 makes you a great fit for our team. Don’t forget to mention any specific projects that relate to the job description.
Showcase Your Technical Skills: In your application, be sure to showcase your technical skills clearly. Mention your proficiency in Python, SQL, and any experience with data modelling or governance tools. We love seeing concrete examples of your work!
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, we keep an eye on applications that come through our site!
How to prepare for a job interview at Quantios
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Microsoft Fabric, Databricks, and Snowflake. Brush up on your Python and SQL skills, and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Data Pipeline Experience
Prepare specific examples of ETL/ELT pipelines you've designed or maintained. Be ready to explain the challenges you faced and how you ensured data quality and governance in your previous roles.
✨Understand Data Modelling Concepts
Familiarise yourself with lakehouse architecture and the medallion approach. Be prepared to discuss how you’ve implemented semantic data models and optimised datasets for analytics tools like Power BI.
✨Emphasise Collaboration Skills
Since this role involves working closely with various teams, think of examples that highlight your teamwork and communication skills. Discuss how you’ve collaborated with architects, product owners, or other stakeholders to deliver data solutions.