Associate - Data Engineer - Global Master Data

Eli Lilly and Company • Indianapolis, IN

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About The Position

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. What You Will Do As a Data Engineer you will be located in Indianapolis, IN and responsible for designing, developing, and maintaining the data solutions that ensure the availability and quality of data for analysis and/or business transactions. They design and implement efficient data storage, processing and retrieval solutions for datasets and build data pipelines, optimize database designs, and work closely with data scientists, architects, and analysts to ensure data quality and accessibility. Data engineers require strong skillsets in data integration, acquisition, cleansing, harmonization, and transforming data. They play a crucial role in transforming raw data into datasets designed for analysis which enable organizations to unlock valuable insights for decision making. Design, build, and maintain scalable and reliable data pipelines for batch and real-time processing. Own incident response and resolution, including root cause analysis and post-mortem reporting for data failures and performance issues. Develop and optimize data models, ETL/ELT workflows, and data integration across multiple systems and platforms. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions. Implement data governance, security, and quality standards across data assets. Lead end-to-end data engineering projects and contribute to architectural decisions. Design and implement cloud-native solutions on AWS (preferred) using tools such as AWS Glue, EMR, and Databricks. Experience with Azure or GCP is a plus. Promote best practices in coding, testing, and deployment. Monitor, troubleshoot, and improve performance and reliability of data infrastructure. Automate manual processes and identify opportunities to optimize data workflows and reduce costs. How You Will Succeed: Deliver scalable solutions by designing robust data pipelines and architectures that meet performance and reliability standards. Collaborate effectively with cross-functional teams to turn business needs into technical outcomes. Lead with expertise, mentoring peers and driving adoption of best practices in data engineering and cloud technologies. Continuously improve systems through automation, performance tuning, and proactive issue resolution. Communicate with clarity to ensure alignment across technical and non-technical stakeholders. About the Tech at Lilly Organization: Tech at Lilly builds and maintains capabilities using cutting edge technologies like most prominent tech companies. What differentiates Tech at Lilly is that we create new possibilities through tech to advance our purpose – creating medicines that make life better for people around the world, like data driven drug discovery and connected clinical trials. We hire the best technology professionals from a variety of backgrounds, so they can bring an assortment of knowledge, skills, and diverse thinking to deliver innovative solutions in every area of the enterprise. 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 is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women’s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups. At Lilly we strive to ensure our employees are part of a team that cares about them and our shared purpose of making life better for those around the world. How do we do this? We continue to look for ways to include, innovate, accelerate and deliver while maintaining integrity, excellence and respect for people. We hope that you seek to join us on our journey as we create medicine and deliver improved outcomes for patients across the globe!

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Management Information Systems or similar stem fields
• At least 2 years of experience in data engineering
• 1+ years of experience using GitHub and CI/CD pipelines for code deployment.
• Proven experience in architecting and building high-performance, scalable data pipelines following Data Lakehouse, Data Warehouse, and Data Mart standards.
• Strong expertise in data modelling (both OLTP and OLAP), managing large datasets, and implementing secure, compliant data governance practices.
• Qualified applicants must be authorized to work in the United States on a full-time basis.
• Strong proficiency in SQL and Python.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and tools like Glue, EMR, Redshift, Lambda, or Databricks.
• Deep understanding of ETL/ELT workflows, data modelling, and data warehousing concepts.
• Familiarity with big data and streaming frameworks (e.g., Apache Spark, Kafka, Flink).
• Knowledge of data governance, security, and quality practices.
• Working knowledge of Databricks for building and optimizing scalable data pipelines and analytics workflows.
• Experience with CI/CD, version control (Git), and infrastructure-as-code tools is a plus.
• A problem-solving mindset, attention to detail, and a passion for clean, maintainable code.
• Strong communication and collaboration skills to work with both technical and non-technical stakeholders.

Nice To Haves

• Domain experience in healthcare, pharmaceutical (Customer Master, Product Master, Alignment Master, Activity, Consent), or regulated industries is a plus.
• Partner with and influence vendor resources on solution development to ensure understanding of data and technical direction for solutions as well as delivery
• AWS Certified
• Databricks Certified
• Familiarity with AI/ML workflows and integrating machine learning models into data pipelines
• Experience in leading a small team of data engineers and providing technical mentorship.
• Ability to collaborate with business stakeholders to translate key business requirements into scalable technical solutions.
• Familiarity with security models and developing solutions on large-scale, distributed data systems.

Responsibilities

• Design, build, and maintain scalable and reliable data pipelines for batch and real-time processing.
• Own incident response and resolution, including root cause analysis and post-mortem reporting for data failures and performance issues.
• Develop and optimize data models, ETL/ELT workflows, and data integration across multiple systems and platforms.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions.
• Implement data governance, security, and quality standards across data assets.
• Lead end-to-end data engineering projects and contribute to architectural decisions.
• Design and implement cloud-native solutions on AWS (preferred) using tools such as AWS Glue, EMR, and Databricks. Experience with Azure or GCP is a plus.
• Promote best practices in coding, testing, and deployment.
• Monitor, troubleshoot, and improve performance and reliability of data infrastructure.
• Automate manual processes and identify opportunities to optimize data workflows and reduce costs.

Benefits

• Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).
• In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level