At a Glance
- Tasks: Build and optimise data pipelines using AWS tools while collaborating with engineering and AI teams.
- Company: Creditsafe is a leading provider of business credit reports, transforming data collection and delivery.
- Benefits: Enjoy a supportive culture, opportunities for learning, and access to cutting-edge AI tools.
- Why this job: Join a tech-driven team that values innovation and empowers you to experiment with Generative AI.
- Qualifications: Experience in data engineering, proficiency in Python and SQL, and a passion for AI are essential.
- Other info: No prior GenAI experience needed; curiosity and a growth mindset are what we value most.
The predicted salary is between 36000 - 60000 £ per year.
About Us
We’re Creditsafe – the world’s most-used provider of business credit reports, serving over 100,000 customers globally. But we’re not just about data—we’re a technology-first, product-led organisation undergoing a transformation. Our teams are reimagining how data is collected, modelled, and delivered, and Data Engineering is at the core of this evolution. We’re investing heavily in scalable cloud platforms, Data Vault architecture, and the next generation of engineering tools and techniques—from intelligent developer environments to GenAI-assisted documentation and code acceleration. Our goal is to keep our engineers ahead of the curve, empowered with modern workflows that reduce friction and increase impact.
What You’ll Be Doing
As a Data Engineer, you’ll work on a modern, AWS-native data platform, building high-performance pipelines and collaborating across engineering, analytics, and AI teams to make data accessible, trusted, and intelligent. You will:
- Build, maintain, and optimise batch and streaming pipelines using AWS Glue, Athena, Redshift, and S3.
- Use prompt engineering techniques to guide the behaviour of LLMs in automation, testing, and documentation.
- Partner with platform teams to incorporate GenAI assistants like Cursor, Claude, and Gemini into developer workflows.
- Help curate high-quality datasets, managing structured and unstructured inputs across domains and jurisdictions.
- Contribute to metadata enrichment, lineage tracking, and discoverability using DBT, Airflow, and internal tools.
What You Bring
- Proven experience in data engineering or analytics engineering roles.
- Proficiency in Python and SQL, with strong debugging and performance tuning skills.
- Experience building cloud-native pipelines using AWS tools (Glue, S3, Athena, Redshift, Lambda).
- Familiarity with orchestration tools (Airflow, Step Functions) and DevOps practices (CI/CD, IaC).
- A genuine interest in Generative AI and a desire to grow your skills in areas like prompt engineering, LLM integration, and AI-augmented workflows.
- Comfort collaborating across functions and sharing knowledge with others.
Nice to Have
- Some exposure to GenAI tools (LangChain, LlamaIndex, or open-source LLMs)—but curiosity and a growth mindset matter more than direct experience.
- Familiarity with data cataloging tools (e.g., OpenMetadata, DataHub) and Data Vault methodology.
- Interest in intelligent developer environments (e.g., Cursor, GitHub Copilot, Gemini Code Assist).
- Enthusiasm for creating high-quality, reusable data assets that power both people and machines.
Why Join Creditsafe?
You’ll work in a global business that’s investing in modern, AI-driven data architecture. We’re embedding next-generation tooling—including LLM-powered assistants, metadata-aware pipelines, and intelligent developer environments—into our engineering culture. We understand that not everyone’s had a chance to use GenAI professionally yet—we’ll give you that opportunity. You’ll be given space to experiment, drive innovation, and help define best practices around AI and data. A supportive, international culture that rewards initiative, curiosity, and growth.
Ready to Make the Leap into GenAI? Apply now and help bring intelligence, automation, and creativity into every step of the data lifecycle.
Contact Detail:
Creditsafe Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with AWS tools like Glue, S3, and Redshift. Having hands-on experience or even personal projects showcasing your skills with these platforms can set you apart from other candidates.
✨Tip Number 2
Brush up on your Python and SQL skills, especially focusing on debugging and performance tuning. Being able to demonstrate your proficiency in these areas during discussions can significantly boost your chances.
✨Tip Number 3
Showcase your interest in Generative AI by discussing any relevant projects or learning experiences. Even if you haven't worked directly with GenAI tools, expressing curiosity and a growth mindset can resonate well with the hiring team.
✨Tip Number 4
Network with current employees or join relevant online communities to gain insights into Creditsafe's culture and expectations. This can help you tailor your approach and demonstrate your genuine interest in the role.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with AWS tools like Glue, S3, and Redshift. Emphasise your proficiency in Python and SQL, as well as any experience with orchestration tools and DevOps practices.
Craft a Compelling Cover Letter: In your cover letter, express your genuine interest in Generative AI and how you plan to grow your skills in this area. Mention specific projects or experiences that demonstrate your ability to collaborate across functions and share knowledge.
Showcase Relevant Projects: If you have worked on any projects involving data pipelines, cloud-native solutions, or AI integration, be sure to include these in your application. Highlight your role, the technologies used, and the impact of your work.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail, especially around debugging, performance tuning, and prompt engineering techniques. Familiarise yourself with common data engineering challenges and how you would approach them.
How to prepare for a job interview at Creditsafe
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AWS tools like Glue, S3, and Redshift. Highlight specific projects where you've built or optimised data pipelines, as this will demonstrate your hands-on expertise.
✨Emphasise Your Interest in Generative AI
Since the role involves working with GenAI tools, express your enthusiasm for learning and using these technologies. Share any relevant experiences or projects, even if they are self-initiated, to show your proactive approach.
✨Prepare for Collaboration Questions
Creditsafe values collaboration across teams. Be ready to discuss how you've worked with cross-functional teams in the past, particularly in data engineering or analytics contexts, and how you shared knowledge with others.
✨Demonstrate Problem-Solving Skills
Expect questions that assess your debugging and performance tuning abilities. Prepare examples of challenges you've faced in previous roles and how you resolved them, particularly in relation to data quality and pipeline efficiency.