Senior Data Engineer (Databricks & Graph Databases)

Ascent is now part of Acuity Analytics, marking an exciting new chapter with strong global reach, an impressive client base, and ambitious growth plans. Together, we deliver cutting-edge data and digital transformation solutions to high-growth and regulated organisations—combining talent, technology, and deep domain expertise to drive real business impact.

This role focuses on building graph-driven data platforms and backend data services. You will design and implement Python-based services and APIs (e.g. FastAPI) integrated with graph databases to enable advanced analytics, knowledge graph use cases, and API-first data access across complex scientific and business domains.

You will work closely with engineers, data scientists, and business stakeholders to deliver scalable, production-grade data solutions that go beyond pipelines — towards reusable data products and services.

• Design and develop Python-based backend services and APIs (e.g. FastAPI) to expose data products and graph-powered capabilities
• Build and integrate scalable data pipelines using modern data platforms (e.g. Spark/PySpark, Databricks or equivalent where appropriate)
• Develop reusable, API-first data products aligned to business use cases
• Ensure data quality, governance, and observability across pipelines and services
• Work with large and complex datasets in cloud-native environments

• Design and implement graph data models using technologies such as Neo4j
• Enable relationship-driven analytics and knowledge graph use cases
• Develop performant query patterns and API access over connected data
• Design scalable data structures for complex business domains
• Contribute to graph-centric architecture and modelling best practice

• Partner with technical and business stakeholders to understand requirements and translate them into scalable engineering solutions
• Contribute to agile delivery, sprint planning, and technical documentation
• Share knowledge and engineering best practices across the team

• Strong Python engineering experience (backend services, APIs, or data platforms)
• Experience building APIs (e.g. FastAPI or similar frameworks)
• Hands-on experience with graph databases (preferably Neo4j) and connected data models
• Strong SQL and data modelling fundamentals
• Experience with distributed data processing (e.g. Spark/PySpark or equivalent)
• Strong understanding of modern data engineering principles and cloud-native platforms
• Experience working with large-scale enterprise datasets
• Strong communication and stakeholder management skills 

• Experience with semantic knowledge graphs (e.g. Stardog, RDF, SPARQL)
• Exposure to API-first or microservices-based architecture
• Knowledge of Databricks, Delta Lake, or similar data platform tooling 
• Experience in regulated environments (e.g. pharma / life sciences) 

• Agile, collaborative delivery environment
• Strong focus on ownership, quality, and continuous improvement 
• Opportunity to work on modern data, backend, and graph technologies at scale 

People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.
Check out this page for more details.