Data Engineer at Lilly

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Full Time

Start Date

Immediate

Expiry Date

19 Dec, 25

Salary

180400.0

Posted On

20 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, ETL, ELT, Data Architecture, SQL, Python, Apache Spark, Airflow, Cloud Platforms, Data Quality, Data Governance, Data Modeling, NoSQL, CI/CD, Version Control, Containerization

Industry

Pharmaceutical Manufacturing

Description

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. The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support business operations, analytics and reporting. This role requires strong technical expertise in data architecture, ETL/ELT processes, and cloud platforms, along with the ability to collaborate across teams to ensure data quality, accessibility, and performance. What You Will Do: Technical Responsibilities Design and implement robust data pipelines for ingestion, transformation, and publishing of structured and unstructured data. Develop and maintain scalable ETL/ELT workflows using tools like Apache Spark, and Airflow. Optimize database schemas and query performance across relational and NoSQL databases. Ensure data integrity, lineage, and governance through automated validation and monitoring. Collaborate with data scientists, analysts, and architects to deliver curated datasets for analytics and machine learning. Integrate data from several cloud sources (AWS, Azure, GCP). Implement CI/CD pipelines for data workflows and manage versioning of data assets. Cross-Functional Collaboration Partner with business stakeholders to understand data requirements and translate them into technical solutions. Work with DevOps and infrastructure teams to ensure secure and scalable deployment of data services. Contribute to team-wide best practices. What You Should Bring Technical Skills Proficiency in SQL and Python; experience with Scala or Java is a plus. Knowledge of data warehousing, OLAP/OLTP systems, and distributed computing. Hands-on experience with version control (Git), containerization (Docker), and orchestration (Kubernetes). Certifications in cloud platforms (AWS, Azure, GCP) or data engineering tools are a plus. Experience in regulated industries (e.g., healthcare, finance) is desirable. Soft Skills Strong analytical and problem-solving skills. Excellent communication and documentation abilities. Ability to work independently and in cross-functional teams. Adaptability to fast-paced environments and evolving technologies. Commitment to continuous learning and improvement. Your Minimum Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field. 3-5 years of experience in data engineering or related roles. Expertise in data modeling (conceptual, logical, physical, dimensional). Experience with cloud data platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery). Familiarity with data orchestration tools (e.g., Apache Airflow, Prefect). 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. Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $63,750 - $180,400 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).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees. #WeAreLilly

Responsibilities

The Data Engineer will design, build, and maintain scalable data pipelines and infrastructure to support business operations, analytics, and reporting. This role requires strong technical expertise in data architecture and ETL/ELT processes.