Director of Data Engineering - Global Data Organization

Henry Schein

  • Dublin
  • Permanent
  • Full-time
  • 2 months ago
Job DescriptionWe are seeking a highly experienced Director of Data Engineering to define and execute our data engineering strategy, driving the development of robust, scalable, and high-performance data infrastructure. You will lead a talented team of data engineers, ensuring our data ecosystem meets the evolving needs of our enterprise data platform, APIs, advanced analytics, and other business requirements across the organization. Ideal candidates bring deep technical expertise, a proven track record of building high-performing teams, and experience optimizing data solutions within an Azure Databricks environment. You will collaborate closely with cross-functional stakeholders to ensure data initiatives align with broader business objectives, regulatory requirements, and best-in-class industry practices.Key Responsibilities:
  • Strategic Leadership: Develop and implement the vision, strategy, and roadmap for the enterprise data platform (e-procurement, pricing, and additional business functions), ensuring alignment with overall business goals and seamless integration with other technological functions.
  • Team Development: Recruit, mentor, and lead a high-performing team of data engineers, fostering a culture of continuous learning, innovation, and collaboration.
  • Data Infrastructure: Build and maintain scalable data pipelines and infrastructure to power analytics, business intelligence, and delivery of data—optimizing for both efficiency and cost-effectiveness.
  • Cross-Functional Collaboration: Partner with the architectural team, data strategy, data governance, data science, analytics, product management, and infrastructure teams across the global organization to design and implement solutions that maximize data’s strategic value.
  • Data Governance & Compliance: Ensure our enterprise data ecosystem maintains our standard controls for data governance, security, and compliance, ensuring adherence to frameworks like GDPR, HIPAA, and CCPA.
  • Automation & Reliability: Drive automation in data processing and infrastructure management, implementing robust monitoring, alerting, and self-healing capabilities to enhance system reliability.
  • Technology Evaluation: Continuously evaluate, select, and integrate new tools and technologies, ensuring the data engineering ecosystem remains state-of-the-art.
  • Documentation & Enablement: Oversee the creation of comprehensive documentation, training materials, and knowledge-sharing resources to empower teams across the organization.
  • Vendor & Stakeholder Management: Manage relationships with third-party vendors, performing technology assessments and ensuring optimal return on investment.
  • Thought Leadership: Serve as an advocate for data-driven decision-making, championing the strategic value of data engineering and influencing stakeholders at all levels.
Required Qualifications:
  • Education: Bachelor’s degree (Master’s preferred) in Computer Science, Applied Mathematics, Statistics, Machine Learning, or a closely related field (or foreign equivalent).
  • Experience: 10+ years in data engineering, including at least 5 years in a leadership role overseeing large-scale data initiatives.
  • Data Architecture: Proven expertise in managing large-scale data architecture and distributed systems.
  • Cloud Platforms: At least 7 years of hands-on experience with major cloud platforms (AWS, GCP, or Azure) and data technologies (Spark, Kafka, Snowflake, Redshift, Databricks, BigQuery, Hadoop) among others.
  • Programming: Strong proficiency in SQL, Python, Java, or Scala, along with experience in frameworks like Apache Beam, Flink, or Airflow.
  • ETL & Streaming: In-depth knowledge of ETL pipelines, data warehousing, and real-time streaming architectures.
  • Containerization & Orchestration: Expertise with Docker and Kubernetes in data applications.
  • Data Governance & Security: Deep understanding of IAM, encryption standards, and compliance requirements.
  • DevOps & CI/CD: Proficiency in CI/CD practices and DevOps methodologies for data engineering workflows.
  • Leadership & Communication: Exceptional leadership and stakeholder management skills, with the ability to influence diverse teams and executive partners.
Preferred Qualifications:
  • Industry Experience: Background in high-growth, data-driven organizations; healthcare industry experience is a plus.
  • AI/ML & MLOps: Familiarity with AI/ML infrastructure and MLOps tools (e.g., TensorFlow, MLflow, feature stores).
  • Cost Optimization: Experience in optimizing cloud-based data platforms for performance and cost-effectiveness
Henry Schein is committed to the principle of equal opportunities in employment in all spheres of its operation. Henry Schein UK Holdings strives to operate a policy of equal opportunity and not discriminate against any person gender, race, colour, nationality, ethnic or national origin, religion, sexual orientation, marital status, disability, age or any other characteristic protected by law.

Henry Schein