Data Architect

Summary

Join Rackspace Technology as a Data Architect to design and implement scalable data architectures on the Databricks platform. Lead data migration initiatives from legacy systems to a modern Lakehouse architecture. Develop data engineering frameworks and CI/CD pipelines. Implement data catalog solutions and governance frameworks. Provide technical leadership to data engineering teams and mentor junior members. Ensure data architectures meet security, compliance, and performance requirements. Stay current with emerging technologies and industry trends.

Requirements

• Extensive experience in data architecture design and implementation
• Strong software engineering background with expertise in Python or Scala
• Proven experience building data engineering frameworks and reusable components
• Experience implementing CI/CD pipelines for data solutions
• Expertise in infrastructure-as-code and automation
• Experience implementing data catalog solutions and governance frameworks
• Deep understanding of Databricks platform and Lakehouse architecture
• Experience migrating workloads from legacy systems to modern data platforms
• Strong knowledge of healthcare data requirements and regulations
• Experience with cloud platforms (AWS, Azure, GCP) and their data services
• Bachelor's degree in Computer Science, Information Systems, or related field; advanced degree preferred
• Programming languages: Python and/or Scala (required)
• Data processing frameworks: Apache Spark, Delta Lake
• CI/CD tools: Jenkins, GitHub Actions, Azure DevOps

Responsibilities

• Design and implement modern data architectures using Databricks Lakehouse platform
• Lead the technical design of Data Warehouse/Data Lake migration initiatives from legacy systems
• Develop data engineering frameworks and reusable components to accelerate delivery
• Establish CI/CD pipelines and infrastructure-as-code practices for data solutions
• Implement data catalog solutions and governance frameworks
• Create technical specifications and architecture documentation
• Provide technical leadership to data engineering teams
• Collaborate with cross-functional teams to ensure alignment of data solutions
• Evaluate and recommend technologies, tools, and approaches for data initiatives
• Ensure data architectures meet security, compliance, and performance requirements
• Mentor junior team members on data architecture best practices
• Stay current with emerging technologies and industry trends

Preferred Qualifications

• Infrastructure-as-code (optional): Terraform, CloudFormation, Pulumi
• Data catalog tools: Databricks Unity Catalog, Collibra, Alation
• Data governance frameworks and methodologies
• Data modeling and design patterns
• API design and development
• Cloud platforms: AWS, Azure, GCP
• Container technologies: Docker, Kubernetes
• Version control systems: Git
• SQL and NoSQL databases
• Data quality and testing frameworks
• Healthcare data standards (HL7, FHIR, etc.)
• Clinical and operational data models
• Healthcare interoperability requirements
• Healthcare analytics use cases