Lead Data Architect

Henry Schein

17h•$181,026 - $259,094

About The Position

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.

Requirements

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
Strong Python programming skills, with expertise in data manipulation and pipeline development using Pandas, PySpark, NumPy, and SQLAlchemy.
Hands-on experience with Infrastructure as Code (Terraform, CloudFormation).
Outstanding management and leadership skills and ability to attract, retain, motivate, develop, mentor and coach team members for high performance; good conceptual skills
Outstanding 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
Understand, interpret and act on financial information and external trends that contributes to business profitability
Plan, manage and create strategy around complex projects; understand available resources, develop timeline, budget and assign areas of responsibility
Lead teams to achieve company goals and solve complex business issues in creative and effective ways
Mastery planning and organizational skills and techniques
Communicate effectively with senior management and key stakeholders
Excellent negotiating skills and ability to effectively manage strategic alliances, joint ventures and outsourced relationships
Ability to influence, build relationships, understand organizational complexities, manage conflict and navigate politics
Broad professional and managerial skills with a full understanding of industry practices and company policies and procedures
Lead and develop virtual teams
Mastery in multiple technical and business skills
Excellent strategic planning skills
Typically 12 or more years of increasing responsibility and complexity in terms of any applicable professional experience; 7 or more years of management experience.

Nice To Haves

Familiarity with the healthcare data domain with previous experience working with healthcare datasets is a plus
Experience with AI/ML-driven analytics architectures and MLOps frameworks like MLflow or SageMaker.
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).
Typically a Bachelor's Degree or global equivalent in related discipline. Master's degree or global equivalent a plus.

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.