**Neural Nexus - Manager, Data & AI Enablement (AuRA) (L5)** **Location: India** **Join Amgen's Mission of Serving Patients** At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do. Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas - Oncology, Inflammation, General Medicine, and Rare Disease - we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller, happier lives. Our award-winning culture is team-oriented, innovative, and science-based. If you have a passion for challenges and the opportunities that lie within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. **What You Will Do** Let's do this. Let's change the world. In this vital role within **Neural Nexus - AI Data Enablement (AuRA)** , you will be responsible for the **execution and delivery of AI-enabled data foundations and data products** that power commercial analytics and AI use cases across Amgen. This is a **hands-on execution and delivery leadership role** , focused on **building, operationalizing, and managing scalable, governed, AI-ready data solutions** . You will own delivery of assigned workstreams end-to-end, ensuring solutions are implemented on time, meet quality standards, and drive measurable business value. You will also play a key role in ensuring **data stewardship, governance, and FAIR-aligned data practices** , enabling trusted and reusable data assets across AuRA. **Key Responsibilities** **1. End-to-End Delivery of Data & AI Enablement Workstreams** + Lead execution of **AuRA data enablement workstreams** from intake, design, and development through deployment and operationalization. + Deliver **AI-enabled data products and pipelines** that support commercial analytics and downstream applications.



+ Ensure solutions are delivered **on time, within scope, and aligned to business requirements** . + Coordinate readiness activities including **UAT, access provisioning, documentation, and production handoff** . **2. Data Platform Implementation & AI Readiness** + Implement and scale **AI-ready data foundations within AuRA** , integrating structured and unstructured data sources. + Build and manage **reliable, scalable data pipelines** with appropriate monitoring, logging, and versioning. + Support development of reusable capabilities such as: + Data models and curated data layers + Metadata, tagging, and taxonomy frameworks + Data discoverability and access enablement + Ensure data is optimized for **performance, usability, and downstream analytics/AI consumption** . **3. Data Governance, Stewardship & Quality** + Enforce data governance practices including: + Data ownership and stewardship + Data lineage and traceability + Role-based access controls + Ensure adherence to **FAIR principles (Findable, Accessible, Interoperable, Reusable)** and **Clean Core alignment** . + Drive **data quality processes (QC, MDM, affiliation)** to ensure data is business-ready and trusted. **4. Program Execution & Workstream Management** + Manage multiple concurrent workstreams with clear ownership of: + Scope, timelines, risks, and dependencies + Drive structured program execution using **agile and project management best practices** . + Identify and proactively mitigate **delivery risks and bottlenecks** . + Track and report on **delivery health, milestones, and progress** . **5. Cross-Functional Collaboration** + Partner with **Commercial, CD&A;, Analytics, Technology, and Engineering teams** to deliver data solutions aligned to business priorities.



+ Act as a bridge between **business stakeholders and technical teams** , ensuring clarity in requirements and execution. + Coordinate across teams to maintain **execution alignment and delivery velocity** . **6. Adoption & Value Realization** + Enable business and analytics teams to **access and use trusted AuRA data products** . + Support onboarding activities including: + Training sessions + Documentation and data product guides + Working sessions with end users + Track **adoption, usage, and value realization metrics** to measure impact. **7. Continuous Improvement & Change Management** + Support change management by ensuring readiness of **processes, documentation, and communication** . + Gather feedback from users and stakeholders to improve data products and delivery processes. + Contribute to building **repeatable, scalable delivery frameworks** for AuRA data enablement. **What We Expect of You** **Preferred Qualifications** + Strong experience in **data platform implementation and data enablement delivery** + Experience working with **commercial pharma datasets (CRM, claims, HCP/HCO, patient data)** preferred + Solid understanding of: + Data pipelines (ETL/ELT), data modeling, and data integration + Data governance, MDM, affiliation, and data quality frameworks + AI/ML data requirements and data readiness + Experience with modern data platforms (e.g., **Snowflake, Databricks, Airflow** ) and cloud environments + Proven ability to manage **multiple concurrent workstreams and complex dependencies** + Strong program management and execution skills + Ability to translate business needs into **scalable data solutions** + Strong communication and stakeholder management skills **Why This Role Matters** This role is critical to advancing **AuRA as a scalable, AI-ready data enablement layer within Neural Nexus** , enabling: + Faster delivery of high-quality commercial data + Scalable and reusable data products + Improved efficiency of analytics and AI-driven use cases Your work will directly contribute to how Amgen leverages data to improve decision-making and ultimately serve patients better.

📌 Neural Nexus - Data Steward, Data & AI Enablement (AuRA) (Hyderabad)
🏢 AMGEN
📍 Hyderabad