Data Engineer - Snowflake and Databricks

Data Engineer - Snowflake and Databricks

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.

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.
• Implement and optimize ELT processes, source-to-target mapping, and transformation logic.
• 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.
• Experience with Databricks Unity Catalog and data sharing technologies.
• Strong skills in CI/CD (Azure DevOps, GitHub Actions) and version control (GitHub).

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Other - IT Services and IT Consulting

Strong cross-functional collaboration and technical support experience for data scientists, report developers and analysts.