Lead Data Architect

About this role

We are looking for a Lead Data Architect to drive the strategic vision, design, and governance of our enterprise data architecture. This role will be instrumental in aligning data architecture with business objectives, ensuring seamless integration across systems, and optimizing data-driven decision-making. The ideal candidate will have a strong blend of technical expertise, leadership skills, and experience with modern data platforms like Databricks, Snowflake, and cloud-native solutions.

This position is responsible for the overall management and oversight of our global data architecture. The individual will collaborate and build strong relationships across Henry Schein including with business leads and technology product teams, driving data architectures to aid with the implementation of database technologies as enablers for key business capabilities. You blend deep expertise and experience in engineering, technical design, systems and database management with a passion for coaching and mentoring engineering associates.   KEY RESPONSIBILITIES: 

Data Strategy & Enterprise Architecture • Define and implement a scalable, enterprise-wide data architecture aligned with business and technology goals. • Develop a data strategy roadmap, ensuring long-term sustainability, scalability, and efficiency. • Partner with executive leadership, product teams, and engineering to ensure data initiatives drive business value. • Establish enterprise data governance, security, and compliance frameworks leveraging tools like Collibra or Alation.

Technical Leadership & Innovation • Define and implement a scalable, enterprise-wide data architecture aligned with business and technology goals.

• Oversee the design and evolution of data lakes, data warehouses, and cloud-based analytics platforms using Databricks, Snowflake, BigQuery, or Redshift. • Lead the adoption of modern data architecture patterns, including event-driven architectures, real-time data streaming (Kafka, Pulsar), and AI-driven analytics. • Provide guidance on database optimization, indexing, partitioning, and storage strategies for tools like PostgreSQL, MySQL, and NoSQL solutions like MongoDB or Cassandra. • Evaluate emerging technologies, making recommendations for tools and platforms that enhance data capabilities.

Data Engineering & Integration • Direct ETL/ELT strategies, ensuring seamless data flow across systems with Python, Apache Airflow, dbt, or Informatica. • Architect cloud-based solutions (AWS, Azure, or GCP) using services such as AWS Glue, Azure Synapse, and Google Cloud Dataflow to support analytics, AI, and operational use cases. • Ensure API-first design for data integration using GraphQL, RESTful APIs, or event-driven architectures (Kafka, AWS Kinesis, Pub/Sub). • Define and oversee data quality, lineage, and cataloging efforts using Great Expectations, Monte Carlo, or DataHub.

Governance, Security & Compliance • Develop policies for data privacy, access control, and encryption, ensuring compliance with GDPR, CCPA, HIPAA, or other relevant regulations. • Implement enterprise-wide metadata management and data lineage tracking using Collibra, Alation, or Data Catalog solutions. • Drive best practices for data security and compliance audits, leveraging IAM tools and cloud security solutions.

Team Leadership & Collaboration • Lead a team of data architects, engineers, and analysts, mentoring them on best practices. • Act as a liaison between business and technical teams, translating business needs into scalable data solutions. • Champion a culture of innovation, ensuring the data team is adopting cutting-edge methodologies. • Conduct data architecture reviews, ensuring alignment with organizational standards.

SPECIFIC KNOWLEDGE & SKILLS: 

• 10+ years of experience in data architecture, data engineering, or related fields. • Bachelor’s degree (Master’s preferred) in Computer Science, Applied Mathematics, Statistics, Machine Learning, or a closely related field (or foreign equivalent). • Proven track record in designing large-scale, enterprise data architectures. • Expertise in SQL, NoSQL, and distributed database technologies such as Snowflake, Databricks, BigQuery, Redshift, PostgreSQL, MongoDB, and Cassandra. • Strong experience with cloud-based data platforms (AWS, Azure, GCP) and services like AWS Glue, Azure Data Factory, and Google Dataflow. • Deep understanding of data modeling, ETL/ELT processes, and data pipeline optimization using dbt, Apache Airflow, Informatica, or Talend. • Experience with real-time streaming technologies (Kafka, Spark Streaming, Apache Flink, AWS Kinesis). • Strong knowledge of data security, governance, and compliance frameworks. • Excellent verbal and written communication skills and ability to resolve disputes effectively and efficiently • Outstanding presentation and public speaking skills • Mastery independent decision making, analysis and problem-solving skills • Ability to quickly understand and assess complex projects, systems and ecosystems and identify relevant relationships and connections between them • Mastery planning and organizational skills and techniques • Communicate effectively with senior management and key stakeholders • Ability to influence, build relationships, understand organizational complexities, manage conflict and navigate politics • Familiarity with the healthcare data domain with previous experience working with healthcare datasets is a plus • Strong Python programming skills, with expertise in data manipulation and pipeline development using Pandas, PySpark, NumPy, and SQLAlchemy. • Experience with AI/ML-driven analytics architectures and MLOps frameworks like MLflow or SageMaker. • Hands-on experience with Infrastructure as Code (Terraform, CloudFormation). • Familiarity with Graph databases and knowledge graphs (Neo4j, Amazon Neptune). • Certifications in cloud data services (AWS Certified Data Analytics, Google Professional Data Engineer, Databricks Certi

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