Sr. Data Architect - SaaS Data Transformation & Migration

Location: Fully Remote (U.S.)Duration: 6-month contract to start with likely extensionsOverviewWe are seeking an experienced Enterprise Data Architect to support a large-scale platform migration and enterprise data migration initiative.

This role will focus on designing scalable cloud data architectures while leading SaaS data transformation and migration into modern cloud platforms such as Databricks or SnowflakeThe ideal candidate has strong experience modernizing data environments, migrating data from SaaS or legacy platforms, and building enterprise data architectures that support analytics and business intelligence.Key ResponsibilitiesLead platform migration and large-scale data migration efforts from SaaS and legacy systems into modern cloud data platformsArchitect enterprise data solutions across cloud environments such as Databricks or SnowflakeDesign data models, data pipelines, and integration frameworks supporting enterprise systemsImplement SaaS data transformation strategies to support analytics and reportingBuild and optimize cloud data pipelines using tools such as dbt, Fivetran, or similar ELT toolsDesign and implement lakehouse architectures supporting both structured and unstructured dataPartner with engineering, analytics, and business teams to ensure scalable, reliable data architectureRequired Experience5+ years of experience in Data Architecture or Enterprise Data Engineering (10+ preferred)Strong experience with platform migration and enterprise data migrationExperience with cloud data platforms such as Databricks or SnowflakeExperience with SaaS data transformation and migrationExperience with cloud platforms (AWS, Azure, or GCP)Strong knowledge of data modeling, data governance, and data architecture frameworksProficiency with SQL and PythonPreferred ExperienceExperience with lakehouse technologies (Delta Lake, Apache Iceberg, Apache Hudi, Microsoft Fabric)Experience with modern ELT tools such as dbt or FivetranExperience supporting BI tools such as Power BI, Tableau, Looker, or QlikThis is a great opportunity to help drive enterprise platform modernization and cloud data transformation within a large-scale data environment.J-18808-Ljbffr