Senior Principal Data Engineer

The Senior Principal Data Engineer will serve as a senior technical leader responsible for shaping enterprise-scale data architecture and engineering strategy.
You’ll design secure, scalable data platforms that support analytical, operational, and AI-driven workloads across multiple business domains.
The role combines hands-on architecture and engineering with technical governance, standards development, and strategic decision-making.
You’ll champion modern cloud technologies, reusable frameworks, automation, and AI-assisted engineering practices to improve productivity and platform quality.
The position also provides significant technical influence, guiding complex initiatives and mentoring senior and principal-level engineers without direct people-management responsibility.
You’ll collaborate closely with Product, Data Science, Analytics, Data Governance, Enterprise Architecture, and Infrastructure teams.
This is a fully remote U.S. opportunity offering the chance to shape long-term data capabilities in a highly collaborative and innovation-focused environment.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical discipline; a Master’s degree is preferred.

• 7+ years of experience in Data Engineering, Software Engineering, Data Platform Engineering, or a closely related field.

• Extensive experience designing and implementing enterprise-scale cloud data platforms and data architectures.

• Expert-level programming skills in Python and SQL.

• Strong expertise in conceptual, logical, and physical data modeling.

• Hands-on experience with Databricks, Azure, AWS, Docker, Kubernetes, Git, REST APIs, and CI/CD environments.

• Strong understanding of software architecture, design patterns, distributed systems, and secure data platform design.

• Experience establishing engineering standards, governance practices, reusable frameworks, and technical roadmaps.

• Demonstrated ability to lead highly complex technical initiatives through influence, collaboration, and technical credibility rather than direct people management.

• Excellent communication, stakeholder-management, presentation, and technical leadership skills.

• Strong analytical thinking, problem-solving ability, initiative, and results orientation.

• Demonstrated ability to mentor experienced engineers and foster knowledge sharing and engineering excellence.

• Experience working collaboratively across Product, Data Science, Analytics, Governance, Architecture, and Infrastructure functions.

• Preferred experience in pharmaceutical, biotechnology, healthcare, or another regulated industry.

• Preferred experience with Databricks Unity Catalog, enterprise data governance, metadata management, data lineage, and observability.

• Experience with Infrastructure as Code tools such as Terraform, Bicep, or comparable technologies is preferred.

• Experience applying Generative AI to software engineering or data engineering is preferred.

• Commitment to continuous learning, adaptability, inclusive collaboration, clear communication, and innovation.