Senior Specialist, Data Stewardship - Innovation Lead

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. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates 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 companys’ 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 to ensure we can manage and improve each location, from investing in 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. And 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** The Sr. Specialist, Data Stewardship – Innovation Lead is part of the **EDQ&DSC (Enterprise Data Quality and Data Stewardship)** team within the **CDAO (Chief Data and Analytics Office)**. This role is a hands-on opportunity to design, build, and deploy LLM-powered automation and agentic AI solutions that transform data stewardship, improve data quality, and enable scalable governance operations across the enterprise. The individual will work closely with cross-functional partners to deliver reliable, secure, and scalable AI-driven workflows that reduce manual effort, accelerate decision-making, and strengthen stewardship across the data lifecycle. A key focus of the role is to accelerate and scale stewardship through automation and agentic AI by deploying trustworthy, policy-aware AI agents that can plan, act, and learn across data quality, metadata, lineage, R/MDM, access/privacy, and data product operations while maintaining strict guardrails, traceability, and auditability. This role combines data stewardship, software engineering, workflow automation, and responsible AI engineering to support a global, regulated enterprise environment. **What will you do in this role** **Data Stewardship Innovation / Automation** - Maintain a living roadmap of automation opportunities across stewardship workflows, metadata management, data quality, access/privacy, and data product operations. - Prioritize initiatives based on business value, risk reduction, regulatory alignment, and time-to-impact. - Run pilots and proof-of-value initiatives with cross-functional teams, define success criteria, and measure outcomes. - Work with stewardship, governance, and operations teams to create and deploy agents that support data quality and other stewardship processes. **Automation and Agentic AI** - Design and implement automation and agentic AI systems to support data governance, enablement, and stewardship activities. - Develop solution designs using approved architecture patterns, including orchestration logic, tool use, memory strategies, and last-mile automation. - Build production-grade code for automation, AI agents, services, and supporting infrastructure. - Develop agents capable of: - Executing multi-step workflows - Interacting with enterprise data, metadata, and knowledge systems - Reasoning over policies, standards, and governance rules - Escalating decisions or exceptions appropriately **Integration and Platform Enablement** - Integrate automation with catalogs, lineage, data quality, R/MDM, access, and other data platforms. - Define APIs, metadata contracts, and integration patterns that support secure and scalable adoption. - Interact with enterprise APIs, document repositories, and knowledge systems to enable agent-based workflows. - Refactor prototypes into maintainable services suitable for development, test, and production environments. **Production Operations and Scaling** - Package and deploy AI solutions into controlled environments, following software engineering and release management best practices. - Monitor agent behavior, performance, and outputs to ensure reliability, traceability, and policy compliance. - Diagnose and remediate failures, hallucinations, workflow breaks, and data-quality dependencies. - Support the expansion of successful pilots into enterprise standards and reusable platforms. **Governance, Compliance, and Responsible AI** - Implement logging, auditing, explainability, and versioning for AI agents, prompts, and workflows. - Ensure solutions comply with regulatory, security, and internal governance requirements. - Support regulatory and inspection readiness by automating documentation, audit trails, and data validation processes. **Enablement and Adoption** - Drive enablement and change management for adoption through training, job aids, and stewardship playbooks. - Develop technical documentation, architecture diagrams, runbooks, and usage guidance for AI solutions. - Enable other teams to adopt, extend, or integrate AI agents through reusable components and patterns. - Communicate outcomes, lessons learned, and ROI to stakeholders. **What should you have** - Bachelor’s or Master’s degree in Computer Science, Data Science, Bioinformatics, or a related field - 8+ years of experience in AI/ML, data science, or related domains - Experience building or deploying A