Job description

Data Engineer - Snowflake and Databricks job at Expedite Technology Solutions. Seattle, WA. Primary Skill: DBT Labs Snowflake Secondary Skill: Databricks Databricks Unity Catalog Responsibilities: Develop, optimize, and maintain data pipelines using Azure Data Factory (ADF), DBT Labs, Snowflake, and Databricks. Develop reusable jobs and configuration-based integration framework to optimize development and scalability. Manage data ingestion for structured and unstructured data (landing/lake house: ADLS, Sources: ADLS, Salesforce, SharePoint Documents Libraries, Partner Data: Client, IHME, WASDE, etc.). Implement and optimize ELT processes, source-to-target mapping, and transformation logic in DBT Labs, Azure Data Factory, Databricks Notebook, Snow SQL, etc. Collaborate with data scientists, analysts, data engineers, report developers, and infrastructure engineers for end-to-end support. Co-develop CI/CD best practices, automation, and pipelines with Infrastructure engineers for code deployments using GitHub Actions. Bring in automation from source-to-target mappings to data pipelines and data lineage in Collibra. Required Experience: Hands-on experience building pipelines with ADF, Snowflake, Databricks, and DBT Labs. Expertise in Azure Cloud with Databricks, Snowflake, and ADLS Gen2 integration. Data Warehousing and Lakehouse Knowledge: Proficient with ELT processes, *** Tables, and External Tables for structured/unstructured data. Experience with Databricks Unity Catalog and data sharing technologies. Strong skills in CI/CD (Azure DevOps, GitHub Actions) and version control (GitHub). Strong cross-functional collaboration and technical support experience for data scientists, report developers, and analysts. #J-18808-Ljbffr Expedite Technology Solutions

Requirements