Graph Engineer, Data Context Layer

Job description

Job Description **The Opportunity** - Based in Hyderabad, join a global healthcare biopharma company and be part of a 130-year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. - Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. - Drive innovation and execution excellence. Join a team that is passionate about using data, analytics, and insights to drive decision-making and create custom software, allowing us to tackle some of the world's greatest health threats. Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company's IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy. A focused group of leaders in each Tech Center helps ensure we can manage and improve each location, from investing in the growth, success, and well-being of our people to making sure colleagues from each IT division feel a sense of belonging, to managing critical emergencies. Together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers. ## **Role Overview** This role is part of a broader enterprise initiative to establish a **Data Context Layer (DCL)** — a foundational capability designed to provide consistent, reusable, and scalable context across enterprise data products. The DCL is intended to address challenges related to **data fragmentation, lack of shared semantics, and inconsistent interpretation of data across systems and products**. It establishes a unified layer for representing context, relationships, and meaning, enabling downstream products to operate with greater consistency, interoperability, and intelligence. In addition, the DCL plays a critical role in enabling **agentic AI capabilities across the enterprise** by providing the structured context and semantic grounding required for intelligent agents to operate reliably. This includes ensuring that agent-driven workflows and decisions are based on **consistent, governed, and interpretable data context**, reducing risks associated with fragmentation, ambiguity, and lack of control. Within this initiative, we are seeking a Graph Engineer with strong experience in **AWS cloud technologies** and **TIMBR-like tools** to design, build, and maintain the graph and semantic infrastructure that powers enterprise context services, knowledge discovery, and AI-enabled applications. This role focuses on modeling, populating, optimizing, and operationalizing graph-based data structures that make enterprise knowledge more connected, reusable, and actionable. The ideal candidate has hands-on experience with graph data modeling, knowledge graphs, semantic technologies, and cloud-native data platforms. Familiarity with **ontologies, OWL, RDF, agentic AI, prompt engineering, and context engineering** is preferred, as the graph layer may serve both traditional applications and AI/agentic consumers. **What will you do:** ### **Key Responsibilities** - Design and implement graph-based data structures and knowledge graph solutions in AWS and/or TIMBR-like platforms. - Model entities, relationships, and semantic structures that represent enterprise context consistently across domains. - Build and maintain pipelines that ingest, transform, enrich, and populate graph data from source systems. - Collaborate with ontology modelers, data engineers, architects, and platform teams to ensure graph models align with enterprise standards. - Optimize graph performance, query patterns, and data access for downstream applications and APIs. - Support graph validation, versioning, lineage, and operational monitoring. - Work with APIs and context-serving layers to expose graph data to applications, services, and AI/agentic workflows. - Ensure graph assets are production-ready, governed, secure, and maintainable. - Evaluate and apply graph and semantic technologies, including TIMBR-like tooling where relevant. - Help improve how structured context is delivered to prompt-based and agentic systems. **What should you have** ### **Required Qualifications** - 5+ years of experience in data engineering, graph engineering, semantic engineering, or related technical roles. - Strong hands-on experience with **AWS cloud technologies**. - Experience working with graph databases, knowledge graphs, semantic layers, or ontology-driven models. - Familiarity with **TIMBR or TIMBR-like tools** or similar ontology-driven data access platforms. - Strong understanding of graph modeling, entity relationships, and semantic data structures. - Experience building scalable, production-ready data or graph pipelines. - Familiarity with **agentic AI, prompt engineering, and context engineering** concepts. - Ability to collaborate with engineers, architects, and domain experts. ### **Preferred Qualifications** - Experience with AWS services such as S3, Glue, Lambda, Step Functions, DynamoDB, Neptune, Redshift, Athena, or CloudWatch. - Familiarity with RDF, OWL, SPARQL, knowledge graphs, or ontology management tools. - Experience with graph query optimization, data validation, and lifecycle management. - Background in metadata management, master data, or enterprise semantic platforms. - Experience supporting AI-enabled or context-driven applications. - Familiarity with CI/CD, observability, and secure production operations. ### **What Success Looks Like** Success in this role means: - graph structures are accurate, scalable, and aligned with enterprise context