eTeam
Data Engineer
eTeam - Seattle, Washington, us, 98127
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Overview
Job Title:
Data Engineer Location: Seattle WA 98109 (Remote) Duration: 6+ Months
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: DLS, Client, SharePoint Documents Libraries, Partner Data: DHS, 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, Delta 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. .
Primary skills: • DBT Labs • Snowflake Secondary skills: • Databricks • Databricks Unity Catalog
Data Engineer Location: Seattle WA 98109 (Remote) Duration: 6+ Months
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: DLS, Client, SharePoint Documents Libraries, Partner Data: DHS, 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, Delta 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. .
Primary skills: • DBT Labs • Snowflake Secondary skills: • Databricks • Databricks Unity Catalog