Key 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
Qualifications
- 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
Technical Skills
- Programming languages: Python and/or Scala (required)
- Data processing frameworks: Apache Spark, Delta Lake
- CI/CD tools: Jenkins, GitHub Actions, Azure DevOps
- 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
Optional - Healthcare Industry Knowledge
- Healthcare data standards (HL7, FHIR, etc.)
- Clinical and operational data models
- Healthcare interoperability requirements
- Healthcare analytics use cases
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What We Do
At Rackspace Technology, we accelerate the value of the cloud during every phase of digital transformation. By managing apps, data, security and multiple clouds, we are the best choice to help customers get to the cloud, innovate with new technologies and maximize their IT investments. As a recognized Gartner Magic Quadrant leader, we are uniquely positioned to close the gap between the complex reality of today and the promise of tomorrow. Passionate about customer success, we provide unbiased expertise, based on proven results, across all the leading technologies. And across every interaction worldwide, we deliver Fanatical Experience TM — the best customer service experience in the industry. Rackspace has been honored by Fortune, Forbes, Glassdoor and others as one of the best places to work.
