Director, Enterprise Data Architecture

ClinisysMorrisville, NC
$150,000 - $180,000Hybrid

About The Position

As Director, Enterprise Data Architecture, you will lead the enterprise design, governance, and modernization of data platforms and capabilities that enable Clinisys’ digital transformation. This is a transformational leadership role, not a reactive support function. You will partner with Product, Engineering, AI, Cyber Security, and business functions to deliver integrated, end-to-end data capabilities that improve data quality, accessibility, and decision-making outcomes. You will be accountable for both the architecture and the realization of business outcomes enabled by data, including improved data governance, cleanliness, analytics adoption, automation, and availability. The role requires strong cross-functional influence, ownership of enterprise data outcomes, and the ability to drive measurable improvements across the data value chain. Clinisys' AI Philosophy: Building an AI-first organization is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI-enabled, cloud-based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories operate more effectively and generate meaningful insights at scale.

Requirements

  • Proven experience leading enterprise data transformation initiatives with measurable business impact
  • Deep experience with modern cloud data platforms (e.g., Snowflake, Databricks, MS Fabric) including lakehouse, warehouse, ETL/ELT, and streaming architectures
  • Strong understanding of data governance, quality, metadata, lineage, and security practices
  • Experience defining KPIs and driving performance improvements across data and analytics capabilities
  • Strong leadership and influencing skills across cross-functional teams
  • Ability to translate complex data concepts into business outcomes and decisions
  • Bachelor’s degree in Computer Science, Data/Information Systems, Engineering, or related field, or equivalent experience
  • 10+ years of experience in data architecture, data engineering, or data platform leadership
  • 7+ years of experience leading teams and enterprise initiatives

Responsibilities

  • Lead enterprise data architecture and transformation initiatives aligned to business strategy and digital experience priorities
  • Act as a transformation driver by identifying high-impact opportunities to improve data quality, integration, and accessibility across end-to-end workflows
  • Own the enterprise data roadmap including governance, modernization, and platform evolution with clear value realization outcomes
  • Influence cross-functional leaders to align priorities, remove barriers, and accelerate data-driven transformation
  • Lead the design and implementation of scalable data platforms including lakehouse, warehouse, streaming, and integration layers
  • Guide development of robust data pipelines, ingestion frameworks, and enterprise data access patterns
  • Ensure platforms are reliable, secure, and optimized for analytics, AI/ML, and operational use cases
  • Drive standardization and reuse of data architecture patterns across the enterprise
  • Own measurable data outcomes including data quality, governance maturity, availability, analytics adoption, and automation
  • Define and track KPIs such as data completeness, accuracy, latency, accessibility, and usage
  • Establish scorecards and operating reviews to ensure delivery of business outcomes, not just platform deployment
  • Drive continuous improvement across the data lifecycle to reduce friction and improve trust in enterprise data
  • Drive delivery of integrated, end-to-end data capabilities across Product, Engineering, Analytics, and business teams
  • Establish shared accountability for data quality, governance, and experience across functions
  • Communicate data strategy, priorities, and outcomes clearly to executive and technical stakeholders
  • Embed change management and adoption planning to ensure data capabilities are used effectively
  • Implement enterprise data governance frameworks including data quality, lineage, metadata, and access control practices
  • Ensure compliance with data privacy, security, and regulatory requirements in partnership with Cyber Security and Compliance
  • Continuously improve data standards, tooling, and governance practices to support scalability and transformation

Benefits

  • 401 (k) Savings Plan
  • stock incentive programs
  • paid time off
  • parental leave
  • tuition assistance
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