Principal Data Engineer, MS&T Digital Strategy and Process Optimization

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams rich in diversity. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

Position Summary

At BMS, digital innovation and Information Technology are central to our vision of transforming patients’ lives through science. To accelerate our ability to innovate and guarantee supply to our patients around the world, we must unleash the power of technology. We are committed to being at the forefront of transforming the way medicine is made by harnessing the power of computer and data science, artificial intelligence, and other technologies to promote robust products and processes, faster decision making, and more efficient manufacturing and supply.

We are seeking an experienced and highly motivated data engineer to join the Digital Strategy and Process Optimization team within the Manufacturing Sciences & Technology (MS&T) organization. In this role, the Principal Data Engineer will be responsible for designing, building, and maintaining manufacturing data assets and data products to enable rapid investigation resolution and advanced multivariate model development for real-time process monitoring and control.

The ideal candidate will have exceptional background in data engineering (including software engineering principles), data systems, and data governance and will be comfortable working with both structured and unstructured data. Experience in Biopharma manufacturing processes and data types is a plus, but not required.

If you want an exciting and rewarding career that is meaningful and directly helps deliver lifesaving medicines to patients, consider joining our diverse team!

Key Responsibilities

• Work as a member of the MS&T Digital Strategy and Process Optimization team to develop and implement data engineering solutions that deliver high-quality, contextualized datasets as an enabler of advanced process modelling and other analytics
• Design and establish a scalable framework for engineering new features and processing modular datasets across different subject areas into modelling-ready data
• Optimize or redesign existing data engineering solutions to improve efficiency, velocity, and/or scalability, specifically by incorporating software engineering principles
• Collaborate with Data & Supply Technology Excellence (DSTE) team within GPS IT to shape data and technology strategy and drive towards synergistic outcomes
• Devise and implement data engineering best practices across the team with a focus on short-term deliverables and strategic capabilities
• Partner with and guide offshore data partner team who provides support in implementing, maintaining, and supporting data engineering pipeline
• Mentor fellow Data Engineers where required
• Leverage the latest advances in data engineering and analytics to design innovative solutions
• Learn new technologies and lead proof-of-concepts to further innovate and optimize data engineering approaches
• Acquire and maintain thorough understanding of internal and external manufacturing data landscape, including enterprise and site systems, data warehouses, and data lakes

Qualifications & Experience

• Expected 9 years, 4 years with Ph.D., of experience in data engineering or DevOps environment
• Minimum Bachelor’s degree in computer science, information systems, computer engineering, or equivalent experience
• Advanced knowledge of Python or similar data engineering focused programming language
• Hands-on experience implementing and operating cloud-based data ingestion, integration, transformation, storage, and virtualization solutions using company approved technologies such as AWS (Amazon Web Services) native services (S3, Glue, Athena, Redshift, RDS, Aurora, Lambda, SageMaker, EMR, CodeBuild,