Lead Data Architect

Henry Schein

Lead Data Architect driving the strategic vision and governance of enterprise data architecture at Henry Schein. Collaborating with global teams to optimize data-driven decision-making.

Posted 6/13/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $181,026 - $259,094 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSAzureBigQueryCassandraCloudETLGoogle Cloud PlatformGraphQLInformaticaKafkaMongoDBMySQLNeo4jNoSQLNumpyPandasPostgresPulsarPySparkPythonSparkSQLTerraform

About the role

Key responsibilities & impact

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
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
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
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
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

Requirements

What you’ll need

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 Certified Data Engineer)

Benefits

Comp & perks

Medical, Dental and Vision Coverage
401K Plan with Company Match
PTO
Paid Parental Leave
Income Protection
Work Life Assistance Program
Flexible Spending Accounts
Educational Benefits
Worldwide Scholarship Program
Volunteer Opportunities

ATS Keywords

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Hard Skills & Tools

data architecturedata engineeringSQLNoSQLETLELTdata modelingdata pipeline optimizationreal-time data streamingcloud-based data platforms

Soft Skills

communication skillspresentation skillsproblem-solving skillsorganizational skillsdecision makingrelationship buildingconflict managementmentoringinnovationstakeholder management

Certifications

AWS Certified Data AnalyticsGoogle Professional Data EngineerDatabricks Certified Data Engineer