Sr Consultant - Data Spine

Eli Lilly And Company; Bengaluru; On-site; INR 2,800,000 - 4,400,000; Full time

Job summary

Eli Lilly And Company is seeking an experienced Data Spine Operations specialist to ensure accurate implementation of business logic, robust data pipelines, and reliable AI‑enabled analytics. The role bridges business requirements and technical execution across global teams in a pharmaceutical data environment.

You will lead end‑to‑end data operations, perform QA, monitor pipelines, and collaborate with cross‑functional partners to ensure timely, high‑quality insights for commercial analytics

Qualifications

• 6+ years of experience in data/analytics or related field.
• Strong proficiency in SQL and Python for data validation, debugging, and analysis.
• Hands‑on experience with AWS, Databricks, ETL pipelines, Delta Lake, and Lakehouse architectures.
• Demonstrated experience in AI/ML development operations–involving model input validation and data drift monitoring.
• Experience in data testing, scenario validation, anomaly detection, and complex logic implementation.
• Understanding of pharmaceutical commercial data (HCP/HCO, sales, targeting) is a plus.
• Ability to translate functional business logic into scalable technical build requirements.

Responsibilities

• Act as the functional‑technical translator for cross‑functional teams, ensuring business logic is implemented in the Data Spine ecosystem.
• Design and review scalable AWS/Databricks pipelines and metadata flows for AI enablement and analytics.
• Lead end‑to‑end AI/Data Operations: monitoring, validation cycles, and production delivery of insights.
• Perform thorough testing and QA across Data Spine layers for accuracy and stability.
• Troubleshoot operational issues and coordinate with stakeholders to accelerate defect resolution and improve run stability.
• Strengthen data governance with lineage, metadata, and monitoring frameworks.

Skills

SQL

Python

data validation

diagnostics

Education

Bachelor's degree in CS/Engineering/Data/Analytics

Tools

AWS

Databricks

ETL pipelines

Delta Lake

Lakehouse architectures

Job description

Position Summary

As GOSO scales its AI and data operations, this role serves as the hands‑on functional‑technical specialist responsible for ensuring accurate implementation, operational stability, and ongoing performance of all Data Spine‑driven analytics, automations, and AI‑enabled workflows. The role bridges business logic and technical execution across global and local teams, strengthening Data Spine operations, AI Ops rigor, and cross‑functional delivery.

Key Responsibilities

• Act as the functional‑technical translator for IC, SFO, DT, IBU, and Medical teams, ensuring business logic is accurately implemented in GOSO Data Ecosystem and downstream analytical systems
• Design and review scalable AWS/Databricks pipelines, metadata flows, and integration logic, enabling high‑quality data for AI enablement and commercial analytics
• Lead end‑to‑end AI/Data Operations, including pipeline monitoring, anomaly detection, data drift checks, validation cycles, and production execution to ensure reliable delivery of AI‑enabled insights.
• Conduct detailed testing and quality assurance across Data Spine layers to ensure accuracy, stability, and alignment with commercial business rules.
• Troubleshoot and resolve operational issues across upstream and downstream systems, partnering with TL GOSO Stakeholders to accelerate defect resolution and improve run stability
• Strengthen data governance and operational excellence by enhancing lineage, metadata, DQ rules, monitoring frameworks, and standardized operating processes.
• Apply deep knowledge of pharma commercial data (HCP/HCO, sales, targeting, incentives, SFO processes) to ensure technical outputs meet business expectations and drive adoption
• Coordinate across US‑India teams for aligned delivery, SLA adherence, and milestone execution.
• Manage communication and expectations with functional partners, ensuring transparency on issues, timelines, and solution outcomes

Expected Business Outcomes

• Higher trust and accuracy in GOSO insights through precise implementation of business logic across GOSO AI Programs and other data engineering related work
• Accelerated delivery cycles driven by reduced business‑tech handoff gaps and better‑quality upstream requirements.
• Improved stability of Data Spine and AI‑driven analytics due to strengthened validation, monitoring, and operational support.
• Reduced operational disruption and faster delivery of insights across markets, improving adoption of GOSO s data and analytics solutions
• Excellent communication skills with the ability to work across teams and manage stakeholders effectively

Basic Qualifications / Technical Skills

• Bachelor s degree in computer science, Engineering, Data/Analytics, or related field with 6+ years of experience
• Strong proficiency in SQL and Python for data validation, debugging, and analysis.
• Hands‑on experience with AWS, Databricks, ETL pipelines, Delta Lake, and Lakehouse architectures
• Demonstrated experience in AI/ML development operations‑involving model input validation, data drift monitoring, and ensuring data readiness for AI systems
• Experience in data testing, scenario validation, anomaly detection, and complex logic implementation
• Understanding of pharmaceutical commercial data (HCP/HCO, sales, targeting, IC datasets, call/activity data preferred).
• Ability to translate functional business logic into scalable technical build requirements

Additional Skills / Preferences

• Strong analytical, troubleshooting, and problem‑solving abilities.
• Experience supporting production systems or operational data processes.
• Ability to work independently while collaborating effectively with cross‑functional stakeholders.
• High learning agility and ability to handle multiple priorities

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.