Manager, Data Engineering

This position will be remote within the United States

We are looking for a Data Engineering Manager who will lead mission-focused data engineering teams to build high‑availability, global data solutions for consumers and enterprises.

As Data Engineering Manager for our Patient Experience and Analytics Solution, you will be a self‑motivated individual who influences and executes technical strategic objectives, while representing your department across the wider business groups.

This role also functions as a technical leader; you’ll code alongside your team when needed - whether diving into complex problems, reviewing critical implementations, or demonstrating best practices through hands‑on contribution.

The ideal candidate will have experience designing and operating data pipelines at scale, including both real‑time streaming (Kafka) and batch ETL workloads. We are looking for someone with a proven track record working in high‑volume data environments, processing billions of daily messages and managing multi‑terabyte analytical datasets. A strong understanding of data warehouse architecture, change data capture (CDC) patterns, and incremental versus full load strategies is essential for success in this role.

Our teams are mission‑focused and presented with problems, supported by context and research to help them deliver valuable solutions. We are elevating our deployment frequency and technical practices—shipping effortlessly on demand. We seek to master Scrum, and our company operates on a 6‑week cycle that enables us to solve real problems for our users and their patients while balancing technical debt, bugs, innovation, and team growth.

Our teams are directly responsible for making decisions that improve oral care services for thousands of dental professionals and their patients.

• Lead teams of software engineers to improve the lives of Henry Schein One users and their patients through the creation of market‑leading solutions
• Help recruit, develop, and retain engineers to create a high‑performing team
• Oversee team leaders and support them in fulfilling their mission and delivery commitments
• Enable engineering teams to practice continuous delivery at scale by identifying and removing workflow roadblocks
• Inspire, motivate and coach to enable continuous development of team leaders and their teams
• Ensure products are secure, compliant and reliable for Henry Schein One customers
• Collaborate with senior leaders on the vision and strategy for work streams and products
• Partner closely with Product leadership to influence and understand the strategic commitments of your teams
• Build strong cross‑functional relationships and influence others to pursue the best possible user experience
• Enable process and practice maturity to deliver on global growth opportunities
• Positively and collaboratively influence decision‑making to improve practices across your teams, department, and stakeholder network

• Travel typically up to 10% of time
• Office environment with no special physical demands required

• Languages and Frameworks:
  Python, Go, PHP
• Database:
  Redshift, Aurora, Dynamo
  
  DB, MS SQL
• Cloud: AWS, Serverless Architecture, Cloud Formation, Docker
• Big data:
  Kafka, Spark, Py Spark
• Dev Ops:
  Jira, Gitlab CI, npm, Selenium
• Monitoring:
  Dynatrace
• AI:
  Cursor or other AI tools
• Methodologies:
  Agile development, Scrum

• 7+ years of progressive software development and data solution development experience
• 2+ years leading high-performing teams in remote or hybrid environments
• Proven technical expertise with modern development practices and the technologies listed in the section above; able to contribute both code and architecture guidance
• Experience designing and operating large-scale ETL/ELT data pipelines, including real-time streaming (Kafka) and batch processing workloads
• Proven track record working in high-volume data environments processing billions of daily messages and multi-terabyte analytical datasets
• Strong understanding of data warehouse architecture, change data capture (CDC) patterns, and incremental versus full load strategies
• Deep understanding of RESTful API…