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- Tasks: Design and build the first graph-based data architecture for transformative intelligence.
- Company: Join a pioneering NGO focused on tech for good.
- Benefits: Competitive salary, autonomy in projects, and impactful work.
- Other info: Exciting greenfield initiative with significant career growth potential.
- Why this job: Shape the future of AI-driven intelligence and make a real difference.
- Qualifications: Experience with GCP, Neo4j, Python, and data visualisation tools.
The predicted salary is between 65000 - 85000 ÂŁ per year.
Our client is embarking on a genuinely transformative journey and you could be the one who builds the foundation of their entire next-generation data intelligence capability. This is your chance to design and deliver the organisation’s first-ever graph‑based data architecture, shaping how critical intelligence is captured, connected, and exploited.
If you want a role where you own the direction, set the standards, and build something with long‑term impact, this is it.
What You Will Do
- Build Next‑Generation Data Pipelines
- Design and maintain graph‑based ETL pipelines capable of pulling together structured and unstructured data everything from text corpora to company registries, shipping manifests, and financial records.
- Develop robust extraction workflows, integrating third‑party data sources and provider tools.
- Implement data lineage, versioning, and schema governance to ensure full traceability and reproducibility across the entire intelligence lifecycle.
- Engineer Knowledge Graphs From the Ground Up
- Prototype and deploy knowledge graph models linking organisations, facilities, transactions, activities, and more.
- Build clean, maintainable interfaces and APIs for seamless querying across graph and relational environments.
- Integrate visualisation tools (Tableau, MapLibre, bespoke UIs, etc.) to support contextual analysis and intelligence workflows.
- Shape the Future of AI‑Driven Intelligence (Longer Term)
- Prototype and test Model Context Protocol (MCP) servers enabling Natural Language Querying (NLQ) and Natural Language Generation (NLG).
- Support experimentation with NLP and LLM‑driven enrichment alongside analysts and researchers.
- Enable, Support and Uplift the Wider Team
- Provide technical mentorship to analytical and research teams so they can truly leverage the architecture you build.
- Establish best practices for data governance, quality assurance, and documentation.
- Help shape the roadmap for scaling future data engineering capabilities.
What You Will Deliver
- A fully operational graph‑based data pipeline handling heterogeneous sources
- A scalable knowledge graph schema and entity‑relationship model
- A robust lineage and governance framework
- A future‑focused roadmap for team and capability growth
Key Skills and Experience
- Strong hands‑on experience with GCP, Neo4j, Python, and Postgres.
- Familiarity with AI/NLP/LLM integration and data visualisation tools such as Tableau.
- Ability to design and maintain complex data pipelines across structured and unstructured sources.
- Confident working independently, taking ownership of projects, and driving end‑to‑end delivery.
- Comfortable collaborating with analysts and researchers and contributing to best practices in governance and documentation.
What Success Looks Like
- The creation of an intelligence data system that is stable, scalable, queryable, and resilient
- Dramatically improving how fast, traceable, and reliable data‑driven insights can be produced
- Laying the groundwork for a full data engineering function, aligned with strategic growth and evolving mission priorities
You’ll work closely with the Technical Tradecraft Lead, collaborate with research teams, and engage with key integration partners and data providers.
Why This Role Is Truly Appealing
- Build something from scratch
- Own major architectural decisions
- Work across knowledge graphs, graph databases, NLP, and emerging AI interfaces
- See your work used in real operational intelligence
- Define standards, direction, and future hiring
- Have autonomy and real technical influence
This will be one of the most exciting opportunities you’ll see this year. This is not just another data engineering role, it is a greenfield initiative with mission‑level impact.
Not Sure You Tick Every Box? Apply Anyway.
Studies show that women often apply only when they meet 100% of the criteria, whereas men tend to apply at 60%. If you feel you have most of what we’re looking for and believe you’d thrive here, we want to hear from you.
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Information Technology and Research
Industries: Information Services and IT System Data Services
Location: London, England, United Kingdom
Data Engineer in London employer: Inara
Contact Detail:
Inara Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data pipelines and graph-based architectures. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss how you've tackled challenges in previous roles. Confidence is key!
✨Tip Number 4
Don't hesitate to apply through our website! We love seeing passionate candidates who are eager to make an impact. Even if you don't tick every box, if you think you can thrive in this role, we want to hear from you!
We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for data engineering shine through! We want to see how excited you are about building innovative systems and making a real impact in the NGO sector.
Tailor Your CV: Make sure your CV highlights relevant experience with GCP, Neo4j, and Python. We’re looking for specific examples of how you've designed and maintained data pipelines, so don’t hold back on those details!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share your vision for graph-based data architecture and how you can contribute to our mission. Keep it engaging and personal!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Inara
✨Know Your Tech Stack
Make sure you’re well-versed in GCP, Neo4j, Python, and Postgres. Brush up on your knowledge of graph-based data architectures and be ready to discuss how you've used these technologies in past projects. This will show that you can hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in building data pipelines or knowledge graphs. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how you approached problems and what impact your solutions had.
✨Understand the Mission
Research the NGO's mission and values. Be prepared to explain how your work as a Data Engineer can contribute to their goals. Showing genuine interest in their cause will set you apart and demonstrate that you’re not just looking for any job, but this job.
✨Ask Insightful Questions
Prepare thoughtful questions about the role, team dynamics, and future projects. This not only shows your enthusiasm but also helps you gauge if the company culture aligns with your values. For example, ask about their approach to data governance or how they envision the evolution of their data capabilities.