Data Engineer

Qualitest is looking for a senior AI-Native Data Engineer to join the Governance Technology Team within our clients Research’s Risk, Resiliency & Regulatory Governance organisation. This team is focused on building the next generation of governance infrastructure to support AI governance, risk management, security, privacy, and regulatory oversight across Research and Labs product areas. In this role, you will be responsible for designing and scaling robust data pipelines and governance graph architectures that enable structured oversight of datasets, models, systems, approvals, controls, and risks. You will work closely with cross-functional stakeholders including ML Engineers, Security Engineers, Privacy Engineers, TPMs, and Product teams to operationalise graph-based governance solutions across highly complex technical environments. The position sits at the intersection of large-scale data engineering, AI systems, graph technologies, and governance frameworks within a highly innovative and fast-paced environment., * Design, build, and maintain scalable batch and streaming data pipelines using internal and cloud technologies

• Develop and evolve governance knowledge graphs representing datasets, models, approvals, systems, controls, and risk relationships
• Create unified data models to map relational and structured data into graph-based architectures
• Partner with governance stakeholders including security, privacy, legal, and risk teams to define graph ontology and schema requirements
• Establish and maintain data quality, integrity, lineage, and governance controls across pipelines and graph systems
• Support GraphRAG implementations using vector search, graph databases, and semantic search technologies
• Build and manage orchestration workflows using technologies such as Dataflow, Vertex AI, Cloud Composer (Airflow), and Plx Workflows
• Leverage AI-assisted development tooling and automated engineering workflows to improve engineering efficiency and delivery quality
• Contribute to CI/CD, automated testing, infrastructure as code, and software engineering best practices

Do you have experience in Test automation?, * 5+ years of experience within Data Engineering, Backend Engineering, or Data Architecture environments

• Experience working with cloud data platforms, ideally within GCP environments including BigQuery, Dataflow, and Vertex AI
• Strong understanding of graph databases, graph data modelling, ontology design, and graph query languages such as GQL, Cypher, or SQL/PGQ
• Expert-level Python and SQL skills
• Strong understanding of data governance principles including data quality, metadata management, lineage, privacy, and security
• Experience working with modern SDLC practices including CI/CD, automated testing, and version control
• Experience using AI-assisted engineering and development tooling within engineering workflows

Preferred Experience

• Experience with Spanner Graph and/or BigQuery Graph
• Familiarity with vector databases and embedding generation pipelines
• Experience with multi-agent orchestration frameworks such as LangGraph
• Exposure to policy-as-code frameworks
• Experience with data cataloguing and automated lineage tooling
• Academic background in Computer Science, Data Science, Mathematics, or related technical disciplines