Director, Enterprise Data & Analytics Architect - Lilly USA Commercial

Lilly; Bengaluru; On-site; INR 5,000,000 - 8,000,000; Full time

Job summary

Lilly seeks a Director Enterprise Data & Analytics Architect to design and scale a cloud-based Data Intelligence platform using Databricks Lakehouse on AWS. Lead enterprise data governance, AI readiness, and data product development across LillyUSA commercial domains including Sales, Marketing, and HCP engagement.

The role requires 15+ years in data engineering/architecture with deep AWS and Databricks expertise, strong PySpark/SQL skills, and the ability to drive cost-optimized, secure data

Qualifications

• 15+ years in Data Engineering / Architecture roles with 6+ years of hands-on AWS & Databricks experience.

Responsibilities

• Own end-to-end architecture decisions for enterprise data platforms supporting LillyUSA commercial domains.
• Define data platform strategy, semantic layer, ontologies, knowledge graphs, and reference architectures for AI-driven ecosystems.
• Drive adoption of modern data architecture patterns (Data Mesh, Lakehouse, Data Products).
• Collaborate with data scientists and ML engineers to operationalize models and ensure governance and security.

Skills

PySpark

SQL

Delta Lake

Unity Catalog

AWS

Data Modeling

Education

Bachelor's or Master's in Computer Science/Engineering

Tools

Databricks

AWS

Redshift

S3

Glue

DataFactory

Job description

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless workbut its work worth doing. If youre driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Job Title: Director Enterprise Data & Analytics Architect, Lilly USA

Location: Bangalore, India

Employment Type: Full-Time

Experience: 15+ Years

Path Level : P4

About the Role

The Director Lilly USA Data & Analytics Enterprise Architect will play a pivotal role in designing and scaling Lillys Data Intelligence & AI platform on cloud environments such as AWS. This role focuses on leveraging deep Databricks Lakehouse expertise to deliver secure, scalable, and high-performing data architectures including AI/ML, analytics, and data product development across LillyUSA Commercial Technology, enabling smarter sales execution, customer engagement, and commercial analytics. The ideal candidate will blend deep technical expertise, data platform design experience, and strategic vision to enable LillyUSAs transformation into an AI-driven enterprise.

Key Responsibilities

Enterprise Ownership & Accountability

Own end-to-end architecture decisions for enterprise data platforms supporting LillyUSA commercial domains including Sales & Marketing, HCP Engagement, iQ Analytics, and Commercial Operations.Define data platform strategy, semantic layer, ontologies, knowledge graphs, and reference architectures for AI-driven ecosystems that serve LillyUSAs commercial intelligence platforms.Drive adoption of modern data architecture patterns (Data Mesh, Data Products, Lakehouse, Medallion)Translate business priorities into data platform investments with measurable outcomes, including LillyUSA commercial priorities such as next-best-action, HCP segmentation, sales forecasting, and promotional effectiveness

Platform & Architecture Leadership

Design, implement, and optimize Lakehouse architectures using Databricks, Delta Lake, and Unity Catalog across LillyUSAs AWS-based data platform, ensuring alignment with LUSA commercial data products and the IRIS Redshift analytical layer.Operationalize data pipelines, Observability (data + platform monitoring) to optimise cost, infrastructure & resources along with FinOps accountability for LillyUSA commercial workloads.Ensure architectural alignment with cloud security, governance, and compliance standards including GxP, HIPAA, and Lillys internal data governance policies applicable to US commercial data.Strengthen AI Agents / GenAI / Future AI Readiness

Strengthen AI Agents / GenAI / Future AI Readiness

Collaborate with LillyUSA Data Scientists, ML Engineers, and AI Product Teams including the iQ, Venturo, and Commercial Technology practices to operationalize models using Databricks MLflow and Feature Store.Design data readiness pipelines that enable AI/ML experimentation, model training, and inference for LillyUSA commercial use cases such as promotional response modelling, territory planning, and patient identification.Implement MLOps practices for reproducibility, monitoring, and lifecycle management of ML models.3. Data Governance & Optimization

Data Governance & Optimization

Implement data access, lineage, and stewardship frameworks using Unity Catalog, Purview, or AWS Glue Data Catalog, aligned to LillyUSAs Master Data Management (MDM) standards and HCP/HCO data governance requirements.Optimize Databricks performance, scalability, and cost through intelligent cluster configuration and workload tuning.Champion metadata management, data observability, and quality frameworks to support enterprise-grade reliability.4. Collaboration & Leadership

Collaboration & Leadership

Partner with LillyUSA Product Owners, Business SMEs, and Cloud Architects spanning Sales, Marketing, Market Access, and Commercial Operations to design domain-aligned, reusable data products.Mentor and guide engineers on data engineering and cloud platform best practices.Serve as a technical thought leader for LillyUSA Commercial Technology, influencing data architecture standards and the AI-enablement roadmap across LUSA sales, marketing, and customer engagement platforms.Required Skills & Qualifications

Required Skills & Qualifications

Bachelors or Masters degree in Computer Science, Engineering, or related discipline.15+ years in Data Engineering / Architecture roles with 6+ years of hands-on AWS & Databricks experience.Strong proficiency in PySpark, SQL, Delta Lake, and Unity Catalog.Proven experience in designing and managing data solutions on AWS (e.g., S3, Redshift, Glue, Data Factory, Synapse).Deep understanding of data modelling, ETL orchestration, and performance .