Director, Engineering

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When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

In this role, you will lead data and software engineering teams responsible for delivering secure, reliable, and high-value Procedural Analytics (PA) data products for Vizient and its members. You will own the engineering execution for PA data pipelines and enrichment services, partnering closely with Product Management, Analytics, and Enterprise Architecture to translate product strategy into scalable, cloud-native data solutions.

This role blends people leadership, strong technical depth in data engineering, and architectural ownership within the PA domain. You will drive engineering excellence, operational reliability, and platform modernization while developing teams and delivering consistent business value.

• Lead and develop high-performing data and software engineering teams responsible for building, testing, and operating Procedural Analytics data pipelines and services.
• Own the end-to-end engineering lifecycle for PA data products, including ingestion, distributed processing, enrichment, and delivery to downstream analytics, reporting, APIs, and UI consumers.
• Partner closely with Product Management to translate PA product strategy and roadmaps into clear technical plans, delivery commitments, and high-quality solutions.
• Collaborate with Solution Architects and Enterprise Architects to ensure PA solutions align with Vizient architecture standards while meeting performance, scalability, and reliability needs.
• Serve as the primary technical point of accountability for PA engineering teams, including architecture decisions within approved enterprise guidelines.
• Ensure strong engineering standards for data quality, security, reliability, scalability, observability, and compliance across all PA pipelines.
• Own accountability for data correctness, timeliness, and operational reliability, including pipeline SLAs, data freshness, and cost awareness.
• Lead incremental modernization of PA BDP pipelines to the Tech Core platform architecture, balancing delivery needs with technical debt reduction.
• Champion modern data engineering practices, including Azure-native development, Databricks and Spark-based processing, standardized CI/CD pipelines, automated testing, and proactive monitoring.
• Act as an escalation point for complex technical or data-quality issues, guiding teams through resolution and post-incident learning.
• Encourage responsible adoption of AI-assisted development tools to improve productivity while maintaining strong engineering judgment and quality standards.
• Lead hiring, onboarding, performance management, and career development for engineers, building strong teams and future leaders.
• Foster an inclusive, collaborative engineering culture that values accountability, continuous improvement, and partnership with product and analytics stakeholders.
• Communicate engineering priorities, progress, and risks clearly to leadership and cross-functional partners.

• 7 or more years of experience building and operating large-scale data or software systems in production environments.
• 3 or more years of experience leading engineering teams, including direct people management responsibilities.
• High School diploma required, Bachelor’s degree in Computer Science, Engineering, or a related field preferred.
• Strong hands-on experience with Azure Databricks, PySpark, and Python, including building and operating production‑grade distributed data pipelines.
• Solid understanding of Delta Lake concepts such as ACID transactions, schema evolution, and data versioning.
• Experience working with cloud‑native data architectures on Microsoft Azure.
• Ability to guide teams on Python data engineering best…