Data Architect (Data Platform)

Position:  Data Architect (Data Platform) Location:  Salt Lake City, UT Job Id:  1169 # of Openings:  1 Job Title:  Data Architect (Data Platform)   Job Summary:  As a Data Architect for healthcare applications, you are responsible for innovating, designing and managing scalable, secure, and interoperable data systems that support clinical, operational, and financial workflows. This role focuses on structuring complex healthcare data from electronic health records (EHRs) to healthcare financial data into cohesive architectures that enable accurate reporting, analytics, and patient care insights. This role will ensure compliance with healthcare regulations such as HIPAA, implement industry standards like HL7 and FHIR for seamless data exchange, and establish strong data governance, quality, and security practices such as HITRUST. By aligning data strategy with organizational goals, this role plays a critical part in improving data accessibility, reliability, and ultimately patient outcomes.   Data Modeling & Design You need to be fluent in conceptual, logical, and physical data modeling. That includes understanding normalization vs. denormalization, dimensional modeling (star/snowflake schemas), and designing for scalability and performance.   Database & Storage Expertise Deep knowledge of both relational and non-relational systems is critical. This also means familiarity with data lakes, lakehouses, and distributed storage systems/warehouses (e.g., S3, Delta Lake, BigQuery)   Data Integration Designing pipelines that move and transform data reliably. This includes experience with ETL/ELT tools (DBT), streaming systems (Kafka, Kinesis), and orchestration frameworks (Airflow, etc.) with the ability to understand batch vs. real-time tradeoffs   Performance Optimization Indexing strategies, partitioning, query tuning, and workload. The ability to architect for scale, resiliency and business continuity.   Strategic Thinking Beyond solving today’s problems, you will define our data strategy including: Define what the future data architecture should look like Determine how and where to reduce technical debt Identify how to enable analytics insights, incorporate AI, and drive self-service?   Artificial Intelligence (AI) Define and evolve data architectures that support AI/ML workloads, including curated training datasets, feature stores, and scalable pipelines for batch and real-time inference Define and evolve data architectures that leverage AI to drive greater operational efficiency, reduce system complexity, and accelerate the ingestion and processing of healthcare data across platforms Design scalable pipelines and platforms (e.g., lakehouse, streaming, feature stores) that enable faster data availability for AI-driven insights and real-time decision support   Minimum Requirements: Specific Job Skills: 12+ years of software engineering experience, including hands-on technical experience building, maintaining and scaling data systems. 5+ years of experience as a tech lead who successfully converts business / product requirements into well architecture designs. Extensive experience in building and scaling large data pipelines including real time processing and / or 100+ GB transformation in Java, Python, DBT, and SQL. Extensive experience in building and driving large business outcomes by leveraging a combination of existing and new technologies. A deep knowledge of common data technology stacks such as GCP BigQuery, Snowflake, Databricks, DBT, Datalake architecture on AWS S3 or GCP Cloud storage. A deep knowledge in cloud platforms such as AWS, GCP, or Azure, and cloud-native API solutions. Deep knowledge of data modeling and data governance control Strong RESTful API design principle, microservices architecture, distributed asynchronous system and good design patterns Strong...