At Kodiak Solutions, we’re dedicated to transforming the healthcare industry through cutting-edge, technology-driven solutions. We specialize in healthcare finance, unclaimed property, risk management, and revenue cycle management, helping healthcare organizations streamline complex financial operations. Our mission is to simplify and optimize processes, so healthcare providers can focus on delivering excellent patient care.
In this role, you will be responsible for defining, designing and implementing data architecture patterns and frameworks that enable trusted, governed and business ready data and support AI-enabled use cases. The primary focus is to support, enable, and accelerate product development initiatives and broader organization by defining enterprise data management standards, developing models and architectures, establishing governance practices, and optimizing automated data flows across cloud data platforms and modern transformation frameworks.
As a Data Architect, you will evaluate and recommend technology capabilities that align with Kodiak Solutions standards, particularly across Microsoft Azure, Snowflake, Data Build Tool (dbt), Sigma, Acceldata, and related data governance, observability, and analytics platforms. Your work will improve the reliability, scalability, and optimization of our data infrastructure.
Build an expert understanding of Kodiak Solutions’ flagship products and the data capabilities required to support them.
- Define reusable data products, semantic models, and architecture patterns that accelerate product development and analytics delivery.
- Establish data contracts, schema standards, and integration patterns to improve reliability across source systems and consuming applications.
- Lead metadata, lineage, catalog, and data observability strategy to improve discoverability, trust, reuse, and regulatory readiness.
- Define AI-ready data standards, including data quality, access controls, lineage, privacy safeguards, and governance requirements for AI/LLM-enabled use cases.
- Uphold and evolve enterprise data management standards
- Collaborates with data domain teams to refine requirements, and design domain-specific data products
- Enforces and establish standards and data governance practices and maintains the data catalog
- Lead Proof-of-concept initiatives for new architecture approaches
- Lead engineering teams through conceptual, logical, and physical data modeling from requirements through implementation, including entity and relationship definition, normalization and denormalization decisions, naming standards, data types, keys, constraints, and model documentation.
- Optimize and manage ELT/ETL data flows, transformation models, semantic layers, and performance patterns to improve reliability, efficiency, and accuracy.
- Evaluate and recommend technologies aligned with Kodiak Solutions standards, including Snowflake, Azure data services, dbt, Sigma, Acceldata, data catalogs, data observability tools, and AI-enabled data services.
- Collaborate with the Sr. Data Architect, enterprise architecture function, team leads, and data engineers to provide oversight and execute on a long-term data vision.
- Partner with data engineering, analytics, product, security, and governance teams to support trusted self-service analytics and AI/LLM-ready data products.
Qualifications
10+ years of experience across data architecture, data engineering or analytics engineering.
- Expert-level Snowflake experience spanning semantic views and integrations; security controls, including row-level security (RLS), masking policies, and role management; and performance and cost optimization
- Extensive experience in data architecture, with a focus on designing and implementing data frameworks.
- Familiarity with Medallion and Lambda architecture patterns
- Proficiency in developing data models, architecture, and governance procedures.
- Familiarity with modeling techniques for online transaction processing (OLTP) systems and with dimensional modeling for analytics.
- Experience with data modeling and design tools such as Erwin, ER Studio, or comparable modeling platforms.
- Expert level experience with dbt, including incremental model design, custom materialization and test harness strategy,
- Hands-on or architectural exposure to Sigma, Acceldata, Collibra, or related data stack is a plus.
- Experience designing, implementing, or operating SQL Server.
- Experience with CosmosDB or MongoDB is a plus
