Data Solutions Architect

Surescripts serves the nation through simpler, trusted health intelligence sharing, in order to increase patient safety, lower costs and ensure quality care. We deliver insights at critical points of care for better decisions - from streamlining prior authorizations to delivering comprehensive medication histories to facilitating messages between providers.

Job Summary:

The Data Solutions Architect designs and evolves our data architecture on Google Cloud Platform (GCP), enabling scalable, secure, and intelligent solutions that improve healthcare outcomes nationwide.

The Data Solutions Architect translates complex business needs into modern data and system architectures, streamlines data flows across the enterprise, and reduces technical complexity. The role helps shape our future-state architecture with a strong focus on data governance, privacy, security, and AI readiness-ensuring compliance with healthcare regulations like HIPAA while enabling innovation.

Responsibilities:

• Transform product concepts into secure, scalable, and maintainable data architectures that align with enterprise standards and future growth.
• Collaborate with data scientists, engineers, product managers, and business stakeholders to ensure solutions are aligned with strategic objectives and deliver measurable value.
• Convert complex business needs into actionable data and system requirements.
• Develop and manage architecture views that visualize data domains and interactions, minimizing redundancy and simplifying data flows across systems.
• Prototype architectural concepts quickly to validate feasibility, accelerate innovation cycles, and inform decision-making.
• Assess and recommend modern tools and platforms for data storage, processing, analytics, and integration, ensuring alignment with enterprise architecture and governance standards.
• Continuously refine cloud-based data architectures based on evolving business capabilities, stakeholder feedback, governance policies, and privacy/security requirements.
• Participate in early-stage evaluations and demonstrations of emerging technologies to drive innovation and inform architectural direction.
• Lead the development of architectural roadmaps and influence prioritized backlogs, incorporating key technologies, design patterns, frameworks, and standards.
• Support preliminary project scoping and feasibility assessments, providing guidance on data integration, automation, and solution design.
• Champion the integration of metadata requirements into centralized repositories, embedding metadata practices into the software delivery lifecycle.
• Create and maintain comprehensive architecture documentation, including conceptual data models, current/future state system views, integration frameworks, and access models.
• Engage technical and non-technical stakeholders across the organization to ensure alignment and shared understanding.
• Collaborate with Enterprise Architecture, Engineering, Data Governance, Privacy, and AI/ML teams to ensure cohesive and forward-looking data strategies.
• Ensure architectural solutions adhere to HIPAA, HITRUST, SOC2 and other healthcare data privacy and security standards.
• Guide and mentor engineers, analysts, and data scientists on cloud data best practices, fostering a culture of excellence and continuous learning.

• Bachelor's Degree in the field of computer science, information systems, or computer engineering and 8+ years of equivalent work experience.
• 8+ years of experience in a combination of enterprise information or data architecture, and data engineering with at least 3 years in a technical leadership capacity.
• Experience working with data management strategy development especially in regards uses of metadata, data lineage, data security, privacy and data life cycle management.
• Significant understanding of enterprise information management disciplines and practices.
• Basic background in OLAP but with strong knowledge of big data such as Hadoop stack and cloud platforms experience.
• Demonstrated ability to work programmatically in such environments, including but not limited to, automation frameworks utilizing python and jvm based languages.
• Knowledgeable of Google Bigquery platform, Bigtable, BQscript, Dataproc, Cloud composer (Airflow), Vertrx ML, Spark Scala platform.
• Strong knowledge of various Business Intelligence architecture, data warehouse, data marts, data lake, lakehouse, semantic layer and reporting layers.
• Research and data analysis skills.
• Creative thinking and problem-solving abilities.
• Great communication and collaboration skills to work with various levels of enterprise partners.