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.
Translate business logic from IC, SFO, DT, IBU and Medical teams into data build requirements
Design and review AWS/Databricks pipelines, metadata flows and integration logic
Monitor AI/data pipelines for anomalies, data drift and validation issues
Test and QA Data Spine layers against commercial business rules
Troubleshoot upstream and downstream issues and speed up defect resolution
From the employer’s posting
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
Act as the functional–technical translator for IC, SFO, DT, IBU, and Medical teams
Design and review scalable AWS/Databricks pipelines, metadata flows, and integration logic
Lead end-to-end AI/Data Operations, including pipeline monitoring, anomaly detection, data drift checks, validation cycles
Conduct detailed testing and quality assurance across Data Spine layers
Troubleshoot and resolve operational issues across upstream and downstream systems
Education & alternatives
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.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
SQL
AWS
Databricks
Delta Lake
Where the posting names them
- 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
- 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.
- 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—including model input validation, data drift monitoring, and ensuring data readiness for AI systems
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About 50,000 in 2025, up 6% from the year before.Annual report (SEC Form 10-K)
Company
Listed as LLY.
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
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About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
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 work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
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 T@L & 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—including 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
Equal Opportunity Employer
Lilly is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, gender, protected veteran status, disability, or any other legally protected status
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.