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 AI or LLM-based solutions (preferably in a regulated environment). Exposure to healthcare, or life sciences domain is preferred Strong hands-on experience in AI/ML, large language models (LLMs), and workflow automation Experience working with LLM tools, APIs, or agent frameworks such as Gemini or similar technologies Strong programming skills in Python and SQL, with experience in data pipelines and automation. Good understanding of data management, data governance and data stewardship workflows. Experience with machine learning concepts such as anomaly detection and predictive modeling Strong problem-solving, collaboration, and communication skills Ability to work in a cross-functional environment and support technical delivery Preferred Qualifications Familiarity with data governance, stewardship operating models, DAMA-DMBOK framework, or CDMP certification will be advantageous. Familiarity with regulated industries such as healthcare, life sciences, finance, or manufacturing. Experience working in a global or matrixed organization. Direct experience building Agentic AI architectures using frameworks such as LangChain, Semantic Kernel, AutoGen, or similar. Experience with enterprise data catalogs, governance platforms, or knowledge management systems. Primary Skills Agentic Workflow & Systems Design Production‑Grade Development & Operations Data Stewardship, Governance & Policy‑Aware Engineering Iterative Delivery & Quick‑Win Execution Cross‑Functional Collaboration Who we are We are known as Merck & Co., Inc., Rahway, New Jersey, USA in the United States and Canada and MSD everywhere else. For more than a century, we have been bringing forward medicines and vaccines for many of the world's most challenging diseases. Today, our company continues to be at the forefront of research to deliver innovative health solutions and advance the prevention and treatment of diseases that threaten people and animals around the world. What we look for Imagine getting up in the morning for a job as important as helping to save and improve lives around the world. Here, you have that opportunity. You can put your emp