The exciting world of scientific research is fueled by people with a passion for solving complex problems. At Cayuse, we are committed to our customers’ success by empowering organizations to conduct globally connected research that advances their impact on science, discovery and society. We build on that commitment with proven, integrated and easy-to-use technology that delivers exceptional value, and world class service and support that accelerates outcomes.
But we are more than just an empowering platform powered by advanced technologies. We are a collaboration of exceptional, highly skilled people with multi-disciplinary expertise, and are building our team to support our ambitious growth plans. Cayuse’s foundational strength comes from our customer and employee focused values and commitment to industry-leading solutions. It’s an exciting time to become a key member of our growing team.
The Data & Integration Architect at Cayuse is a key technical leader responsible for designing and evolving our multi-tenant Saa S platform's suite-wide data architecture and integration strategy. This role transcends traditional data pipeline and ETL-focused responsibilities, emphasizing a holistic approach to data modeling, API-driven integrations, governance, and scalable architecture patterns. The Data & Integration Architect collaborates with engineering, product, peers in the architecture team, and other stakeholders to create innovative data and integration solutions that deliver a seamless experience for customers while ensuring adherence to best practices in governance, compliance, quality, and performance.
The ideal candidate will have a strong background in data architecture and a broad understanding of modern integration patterns, enabling seamless data exchange between systems, applications, and external services. This is an opportunity to shape the future of Cayuse’s data and integration landscape, ensuring reliability, scalability, security, and business alignment across all products.
Key Responsibilities
Strategic Data & Integration Leadership
Define and drive a comprehensive data and integration strategy aligned with Saa S multi-tenancy, security, and scalability requirements.
Collaborate with product management, engineering leadership, fellow architects, and business stakeholders to design interoperable and future‑proof data and integration solutions.
Establish and evolve the suite’s conceptual, logical, and physical data models, ensuring consistency, flexibility, and efficiency across products.
Develop a unified data model for the suite, defining common entities and relationships across multiple product domains.
Define extensible data architectures, supporting multi‑tenant and customer‑specific configurations (e.g., custom form definitions) without compromising performance.
Lead the development of governance frameworks, ensuring data quality, security, and compliance (including regulatory considerations such as HITRUST, HIPAA, GDPR, and Fed RAMP where applicable).
Guide decisions on database and data management solutions tailored to specific use cases, considering performance, scalability, and cost‑effectiveness.
Design dynamic data extension mechanisms to support customer‑specific tenant requirements (e.g., custom form definitions).
Design and standardize suite‑wide API and data exchange patterns, ensuring seamless integration between products and external ecosystems.
Define and advocate for event‑driven architectures, ensuring scalable and decoupled integrations across Cayuse’s platforms.
Partner with engineering teams to implement high‑performance, scalable APIs for both internal and external use cases, ensuring data consistency and efficiency.
Support decisions on data ingress, egress, synchronization, and replication across the suite.
Partner with stakeholders to ensure alignment between governance and operational data practices.
Balance strategic vision with tactical execution, actively engaging in architecture and design reviews, providing technical leadership and best practices to engineering teams. Balance strategic vision with tactical execution, actively engaging in developing and implementing data models, patterns, and solutions to ensure alignment with suite‑wide objectives.
Deliver reusable data and integration patterns, accelerating product development and improving system maintainability.
Educate and mentor engineers, product teams, and stakeholders on modern data architectures, API design, and integration principles. Work closely with the Data Products Engineering and Data Operations teams to translate the data strategy and roadmap into actionable deliverables, providing technical guidance throughout the development lifecycle.
Execution & Operational Support
Drive hands‑on efforts in conceptual, logical, and physical modeling for complex or strategic use cases.
Partner with SREs and Dev Ops teams to optimize data infrastructure and integration reliability, scalability, and security.
Provide expert guidance on ensuring data quality and integrity across the entire data lifecycle, including customer onboarding, synchronization, and transformation.
Define monitoring, observability, and data lineage strategies, ensuring transparency and operational efficiency.
Skills and Qualifications
Required
Demonstrated success as a Data Architect, Integration Architect, or in a similar role, within a multi‑tenant Saa S environment.
Expertise in data modeling at all levels (conceptual, logical, and physical), including experience with dynamic and extensible models.
Proficiency in database and data management technologies, including relational (e.g., Postgres) and cloud‑native solutions (e.g., Snowflake, AWS RDS).
Deep understanding of API design principles, including REST, bulk file‑based, asynchronous, and event‑driven architectures (e.g., Kafka, AWS Event Bridge).
Deep understanding of data warehouses, including design, optimization, and best practices for analytics.
Experience designing and implementing scalable, tenant‑aware data architectures.
Strong grasp of modern integration patterns, including API gateways, data streaming, and hybrid batch‑stream processing.
Knowledge of modern data governance practices including data security, lineage, observability, and compliance requirements.
Excellent collaboration, communication, and influence skills, with experience working across product, architecture, engineering, and operational teams.
Preferred
Familiarity with AWS data services (e.g., Glue, S3, Athena) and tools like Matillion for data pipeline development.
Familiarity with advanced analytics tools and platforms such as Tableau, Microsoft Power BI, Amazon Quick Sight, Si Sense, and Sigma.
Hands‑on experience with modern data pipeline orchestration tools (e.g., Apache Airflow, AWS Step Functions, Matillion).
Experience designing data strategies for hybrid Saa S products transitioning from legacy solutions.
Knowledge of domain‑driven design and its application to data architecture.
Experience designing and implementing data quality capabilities with orchestration tools (e.g., Apache Airflow, AWS Step Functions) and data observability platforms (e.g., Monte Carlo, Datafold).
Key Outcomes
Suite‑wide data model established, ensuring consistency and flexibility.
Scalable API and integration patterns implemented across Cayuse’s platform.
Clear Data & Integration roadmap defined and aligned with business objectives as well as the Cayuse Saa S Platform Plane and the Cayuse Data Plane.
Governance frameworks adopted, improving data quality, compliance, and security.
Reduced time‑to‑delivery for product teams, leveraging reusable data and integration patterns.
Successful deployment of at least one major Data Plane capability within 12 months.
Increased adoption of shared platform services, reducing duplication and improving suite cohesion.
Measurable improvements in data quality, scalability, and maintainability, tracked through defined KPIs.
Competitive Medical Benefits (PPO + HSA available)
Vision, Dental, Short‑Term Disability fully covered by Cayuse
Unlimited PTO + Holidays + Flexible Work Schedule
Remote Work Stipend
401k with Employer Matching
Quarterly Wellness Reimbursement
Remote Work Environment, supporting the Ultimate Employee Experience
Cayuse does not accept agency resumes. Please do not forward resumes to our jobs alias or any Cayuse employees. Cayuse is not responsible for any fees related to unsolicited resumes.
Our culture is one of inclusion and belonging where everyone feels respected, treated justly, supported and nourished. We all share responsibility for creating and sustaining a work environment where differences are celebrated and we are empowered to strive for excellence. We’re proud to be an equal opportunity employer and actively seek to recruit, develop, and retain a diverse and talented workforce.
The role requires establishing consistency across a suite of products by creating a unified data model. Can you describe a project where you defined a shared, cross‑domain data model used by more than one application or business unit? What specific data entities did you need to standardize? *
Our platform uses many integration styles, from APIs to event streams to batch file transfers. Describe a time when you were responsible for defining and standardizing the patterns (the rules, not just the code) for how data should move between multiple systems or external partners. Provide an example of why you selected a particular pattern for a given solution. *
Our solution is a multi‑tenant Saa S platform spanning multiple products. Describe a project where you designed the data architecture for a multi‑tenant environment. How did you ensure strict data isolation between individual tenants while simultaneously optimizing the use of shared compute and data resources across the entire product suite? What were some of the key considerations and decisions in your solution? *
Our goal for governance is to drive standardization and consistency across our product suite. Tell us about your experience establishing and enforcing architectural standards (for things like Canonical Data Models or integration patterns) across multiple, independent engineering teams. What mechanisms or governance bodies did you use to ensure these standards were adopted? *
What are your compensation requirements? *
We are only considering candidates who are local to the United States. Do you reside in the US? *
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