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Cayuse · 1 month ago

Data and Integration Architect

Chicago, IL

Full-time

Hybrid

Senior Level

Cayuse is a company dedicated to empowering organizations in scientific research through advanced technology and exceptional service. The Data & Integration Architect is a key technical leader responsible for designing and evolving the data architecture and integration strategy for their multi-tenant SaaS platform, collaborating with various teams to ensure robust data solutions and adherence to best practices.

SaaSSoftware

Responsibilities

Define and drive a comprehensive data and integration strategy aligned with SaaS 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 FedRAMP 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

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

Drive hands-on efforts in conceptual, logical, and physical modeling for complex or strategic use cases

Partner with SREs and DevOps 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

Qualification

Data ArchitectureAPI DesignData GovernanceMulti-tenant SaaSData ModelingDatabase TechnologiesIntegration PatternsInfluence SkillsCollaboration SkillsCommunication Skills

Required

Demonstrated success as a Data Architect, Integration Architect, or in a similar role, within a multi-tenant SaaS 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 EventBridge)

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 QuickSight, SiSense, 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 SaaS 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)