At a Glance
- Tasks: Design and maintain data pipelines to transform raw data into valuable insights.
- Company: Join Lilly, a global healthcare leader dedicated to making life better for people worldwide.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on mentorship and career development.
- Why this job: Be part of innovative projects that directly impact healthcare and improve lives.
- Qualifications: Proficiency in SQL and Python, with experience in cloud platforms like AWS or Azure.
The predicted salary is between 30000 - 40000 € per year.
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.
About the Tech@Lilly Organization: Tech@Lilly builds and maintains capabilities using cutting edge technologies like most prominent tech companies. What differentiates Tech@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.
About the Business Function: Tech@Lilly Business Units is a global organization strategically positioned so that through information and technology leadership and solutions, we create meaningful connections and remarkable experiences, so people feel genuinely cared for. The Business Unit organization is accountable for designing, developing, and supporting commercial or customer engagement services and capabilities that span multiple Business Units (Bio-Medicines, Diabetes, Oncology, International), functions, geographies, and digital channels.
The areas supported by Business Unit includes: Customer Operations, Marketing and Commercial Operations, Medical Affairs, Market Research, Pricing, Reimbursement and Access, Customer Support Programs, Digital Production and Distribution, Global Patient Outcomes, and Real-World Evidence.
A Data Engineer is 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.
What you’ll be doing:
- Design, build, and maintain scalable and reliable data pipelines for batch and real-time processing.
- 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.
- Drive cloud-native solutions on AWS, Azure, or GCP using tools like Glue, EMR, Databricks.
- 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.
What You Should Bring:
- 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.
Basic Qualifications and Experience Requirement:
- Bachelor’s degree in Computer Science, Information Technology, Management Information Systems, or equivalent work experience.
- Overall 1‑3 years of experience in data engineering using core technologies such as SQL, Python, PySpark, and AWS services including Lambda, Glue, S3, Redshift, Athena, and IAM roles/policies.
- 1+ years of experience working in Agile environments, with hands‑on experience using GitHub and CI/CD pipelines for code deployment.
- 1+ years of experience with orchestration tools like Airflow for workflow automation.
- 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, managing large datasets, and implementing secure, compliant data governance practices.
- 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.
Additional Skills/Preferences:
- Pharmaceutical or healthcare industry experience.
- 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 Data Engineer - Associate.
- Databricks Certified Data Engineer (Associate or Professional).
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 here 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.
BU Global Data Engineer employer: Eli Lilly and Company
At Lilly, we pride ourselves on being a global healthcare leader that prioritises employee well-being and professional growth. Our collaborative work culture fosters innovation through cutting-edge technology, while our commitment to community engagement and philanthropy ensures that our employees feel valued and connected to a greater purpose. Located in Indianapolis, Indiana, we offer a dynamic environment where data engineers can thrive, develop their skills, and contribute to life-changing solutions for people around the world.
StudySmarter Expert Advice🤫
We think this is how you could land BU Global Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Lilly or in the data engineering field. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio of projects that highlight your data engineering expertise. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Ace the interview! Research common data engineering interview questions and practice your answers. We want to demonstrate not just our technical skills but also how we can collaborate with teams.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the Lilly team.
We think you need these skills to ace BU Global Data Engineer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Junior Data Engineer role. Highlight your experience with SQL, Python, and cloud platforms like AWS or Azure, as these are key skills we're looking for.
Showcase Your Projects:Include any relevant projects or experiences that demonstrate your data engineering skills. Whether it's building data pipelines or working with ETL processes, we want to see how you've applied your knowledge in real-world scenarios.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your skills and experiences, making it easy for us to see how you fit into our team at Tech@Lilly.
Apply Through Our Website:Don't forget to submit your application through our official website! This ensures that your application gets to the right place and helps us keep track of all candidates effectively.
How to prepare for a job interview at Eli Lilly and Company
✨Know Your Tech Inside Out
Make sure you brush up on your SQL and Python skills, as well as your experience with cloud platforms like AWS, Azure, or GCP. Be ready to discuss specific projects where you've built data pipelines or optimised ETL workflows, as this will show your hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled challenges in data engineering. Whether it’s automating processes or improving data quality, having concrete examples will demonstrate your problem-solving mindset and attention to detail.
✨Communicate Clearly
Since you'll be collaborating with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will help you convey your ideas effectively and show that you can bridge the gap between tech and business needs.
✨Emphasise Team Collaboration
Highlight your experience working in Agile environments and leading small teams. Discuss how you've mentored peers or collaborated with cross-functional teams to deliver solutions, as this aligns with the collaborative culture at Lilly.
