Data Warehouse Architect

Moda Health•Portland, OR

1d•$110,750 - $160,000•Remote

About The Position

Let’s do great things, together! About Moda Founded in Oregon in 1955, Moda is proud to be a company of real people committed to quality. Today, like then, we’re focused on building a better future for healthcare. That starts by offering outstanding coverage to our members, compassionate support to our community and comprehensive benefits to our employees. It keeps going by connecting with neighbors to create healthy spaces and places, together. Moda values diversity and inclusion in our workplace. We aim to demonstrate our commitment to diversity through all our business practices and invite applications from candidates that share our commitment to this diversity. Our diverse experiences and perspectives help us become a stronger organization. Let’s be better together. Position Summary The Data Warehouse Architect designs and oversees the architecture of enterprise data warehouse systems, ensuring scalability, performance, and security. This role also builds and optimizes data pipelines consistent with data engineering and analytics engineering best practices, contributing significantly to their development. This is a FT WFH position. Pay Range $110,750.29 - $160,000.00 annually (depending on experience) This role may be classified as hourly (non-exempt) depending on the applicant's location. Actual pay is based on qualifications. Applicants who do not exceed the minimum qualifications will only be eligible for the low end of the pay range. Please fill out an application on our company page, linked below, to be considered for this position. https://j.brt.mv/jb.do?reqGK=27769234&refresh=true

Requirements

10+ years working with large data sets, preferably in healthcare data environments, using relational databases and data warehouses serving teams organization-wide, with Power BI, SAS Enterprise Guide, or other BI tool experience preferred.
10+ years of regular SQL use, with advanced knowledge of query optimization and performance management across on-prem SQL servers and SQL-based cloud data warehouses (Snowflake, Microsoft Fabric/Synapse, BigQuery, Redshift). Experience migrating on-prem databases to cloud data warehouses strongly preferred.
10+ years of experience with data transformation tools, including legacy methods (SSIS, T-SQL stored procedures) and modern tools (dbt, Coalesce, Azure Data Factory, Python).
5+ years of experience working in Agile methodology.
Experience with data pipeline orchestration tools such as SSIS, SQL Agent, Tidal, Airflow, and dbt.
Expert-level knowledge of data architecture principles, dimensional modeling, and enterprise data integration strategies.
Experience collaborating using source version control (SVC) systems like Git, with Azure DevOps experience preferred.
Demonstrated ability to identify opportunities, lead development, and implement data-driven solutions that solve real business problems.

Nice To Haves

Experience with programming languages commonly used for analytics such as Python or R preferred.
Experience working with Azure cloud technologies preferred.

Responsibilities

Architect and design end-to-end data warehouse solutions, including data models, integration patterns, and ELT/ETL frameworks.
Develop, test, and deploy code as needed.
Define architectural standards for ELT/ETL automation and scalability and implement processes leveraging modern orchestration tools.
Lead strategic planning and execution of data platform modernization, including cloud migration and hybrid architecture design.
Develop processes and systems to ensure data quality and accuracy.
Create enterprise-grade data architecture frameworks and guide adoption of next-generation data strategies across the organization.
Collaborate with business and technical teams to translate requirements into scalable long-term architectural solutions and support ongoing data infrastructure needs.
Support the Data Science team in implementing data solutions for complex machine learning problems.
Participate collaboratively in Enterprise Data Warehousing, Business Intelligence, and other Data Management projects.
Collaborate with the enterprise IT organization to integrate the Enterprise Data Warehouse into a Microsoft-heavy technology ecosystem.
Perform other duties as assigned.