Lead Data Architect

Overview

It's More Than a Career, It's a Mission.

Our people are the foundation of our success. By joining our growing team at Sarah Cannon Research Institute (SCRI), a subsidiary of McKesson, you will have the opportunity to become part of one of the largest community-based cancer programs to advance oncology treatments and improve outcomes for cancer patients across the globe. We look for mission-driven candidates who have a desire to advance the fight against cancer and make a difference in the lives of patients diagnosed with cancer every day.

Our Mission

People who live with cancer - those who work to prevent it, fight it, and survive it - are at the heart of every decision we make. Bringing the most innovative medical minds together with the most passionate caregivers in their communities, we are transforming care and personalizing treatment. Through clinical excellence and cutting-edge research, SCRI is redefining cancer care around the world.

• As a Lead Data Architect, you will drive our database strategy across all products, analyzing, designing, and implementing complex systems to support robust, scalable data infrastructure aligned with our mission.

• Design, build, and manage the organization's data infrastructure; create the blueprint for data collection, storage, processing, and usage ensuring accessibility, reliability, and security.

• Develop and maintain documentation for database architecture, procedures, and standards; ensure data is a valuable asset for decision-making and operations.

• Data Strategy: Develop and implement a comprehensive data strategy aligned with business goals, understand data needs, and create a roadmap for effective data management.

• Data Modeling: Design conceptual, logical, and physical data models representing data structure and relationships.

• Data Architecture: Create and maintain the overall data architecture framework, including databases, data warehouses, data lakes, and other data systems.

• Data Mapping: Develop and implement data mapping rules to transform data from source to target systems, ensuring accuracy and consistency.

• Data Integration: Design and implement processes for integrating data from various sources, ensuring consistency and accuracy.

• Data Governance: Establish data governance policies to ensure data quality, security, and HIPAA compliance across all data systems and platforms.

• Technology Evaluation: Evaluate and recommend data management technologies and tools to support the organization's needs.

• Problem Solving: Identify and resolve data-related issues, ensuring data integrity and reliability.

• AI Solutions: Design and implement architectures that integrate AI models with existing data infrastructures, including cloud-native and legacy systems.

• Collaboration: Work with stakeholders, including business analysts, data scientists, and IT professionals, to translate data requirements into technical solutions and influence projects related to data quality and management best practices.

• Minimum of 7 years of experience in enterprise data architecture, including data requirements collection, architecture analysis, evaluation, documentation, data modeling, design, development, model validation, and data integration in modern data platforms (e.g., Azure, Databricks, Snowflake).

• Bachelor's Degree in Computer Science, Information Systems, Engineering, or equivalent experience.

• Minimum 10 years of experience in database engineering/management required.

• Knowledge of software development methodologies (e.g., Agile, Dev Ops, SDLC, CI/CD, Git Hub).

• 7+ years' experience working with data sources (e.g. APIs) and databases such as Oracle, Postgre
  
  SQL, SQL Server, and cloud databases.

• Knowledge of cloud technologies like Azure (Data Factory, Databricks), AWS.

• Strong knowledge of industry best practices - code coverage.

• Strong knowledge of database concepts, data modeling techniques, system performance analysis and tuning, and data warehousing concepts.

• Knowledge of operating systems such as Linux, Unix, and Windows.

• Ability to write complex queries and perform advanced database operations using SQL.

• Expertise in modern cloud-native database solutions.

• Experience with database migration tools and strategies, including zero-downtime migrations and data synchronization.

• Proficiency in infrastructure-as-code and automation tools (Terraform) for database deployment and management.

• Ability to design scalable database architectures that support microservices and distributed systems.

• Experience with database patterns (CQRS, event sourcing, sharding strategies).

• Understanding of data modeling for both relational and No
  
  SQL databases.

Sarah Cannon Research Institute (SCRI) is a leading oncology research organization conducting community-based clinical trials. SCRI focuses on advancing therapies for patients and has conducted hundreds of clinical trials and collaborations across the…