Principal Architect, Data

Thank you for considering a career at Ensemble Health Partners!

Ensemble Health Partners is a leading provider of technology-enabled revenue cycle management solutions for health systems, including hospitals and affiliated physician groups. They offer end-to-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country.

Ensemble keeps communities healthy by keeping hospitals healthy. We recognize that healthcare requires a human touch, and we believe that every touch should be meaningful. This is why our people are the most important part of who we are. By empowering them to challenge the status quo, we know they will be the difference!

O.N.E Purpose:

• Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations.

• Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation.

• Striving for Excellence: Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results.

The Opportunity:

The Opportunity:

As a Principal Data Architect, you will play a pivotal role in shaping the future of our Data Platform that powers our current and future capabilities in EnsembleIQ and Analytics platform. You will be entrusted with the responsibility to set a vision for our data platform and guiding data engineers day-to-day with your technical know-how of all technologies supporting data platform. This role requires a blend of deep technical expertise, strategic vision, strong communication skills, ability to influence organization to drive successful implementations that advance our business objectives.

Key Responsibilities:

• Data Architecture Leadership: Lead the design and implementation of robust, scalable, and secure Data Platform architectures that meet business requirements and industry best practices. Lead the design and implementation of end-to-end data pipelines, ensuring efficient data ingestion, processing, and storage across structured and unstructured data sources.

• Cost Optimization: Analyse Azure and Databricks usage and spending patterns to identify opportunities for cost optimization. Provide architecture recommendations on that  selection and resource allocation to maximize cost efficiency without compromising performance or reliability. 

• Technical Leadership: Lead by example in technical excellence and decision-making. Be the go-to person for complex data engineering challenges and provide strategic direction.  Serve as a trusted advisor to our engineering teams, providing guidance on cloud architecture design, implementation strategies, and best practices. 

• Performance Optimization: Continuously monitor and optimize Databricks environments for performance, scalability, and resilience. Implement solutions to address performance bottlenecks and improve overall system efficiency.  

• Security and Compliance: Ensure that Azure cloud architectures adhere to security and compliance standards, including data encryption, identity and access management, and regulatory requirements. Implement robust security controls to protect sensitive data and mitigate security risks. 

• Documentation and Knowledge Sharing: Create detailed technical documentation, architecture diagrams, and best practice guidelines to facilitate knowledge sharing and ensure consistency across projects. Conduct training sessions and workshops to educate team members on technologies and best practices for Data Platform. 

• Governance & Best Practices: Define and enforce data governance standards, security protocols, and best practices for data management and analytics on the Databricks and Azure platforms.

• Integration & Interoperability: Architect seamless integrations between Databricks, Azure Data Lake, Azure Synapse, and other enterprise data services

• Emerging Technologies: Stay abreast of the latest developments in data technologies, evaluating and integrating them into the platform to enhance capabilities.

• Scalability and Reliability: Design systems that can handle large volumes of data and scale seamlessly. This includes monitoring, observability, planning for redundancy, failover mechanisms, and disaster recovery

Qualifications:

• Experience: 8+ years in data architecture, data engineering, or a similar role with hands-on experience in designing and imp