As a Mid-Level Data Engineer, you will leverage AWS or Azure, with expertise in Data Warehousing, SQL, Python, and Snowflake to solve complex data challenges and optimize big data workflows using Databricks.

The Data Engineer will manage data systems, develop ingestion pipelines, optimize performance, and assist in cloud migration to Snowflake.

Develop software solutions, conduct requirement analysis, automate IT processes, troubleshoot code issues, and document programming code for clients.

The Data Engineer role focuses on backend development, automation, and requires expertise in machine learning, DevOps, and cloud platforms.

The AWS Data Engineer will work on data analytics and engineering for clients, utilizing technologies like Python, SQL, and AWS to deliver scalable data solutions and drive decision-making across the organization.

Lead and deliver data and AI analytics projects, design AI-driven solutions, drive cloud transformation initiatives, and manage cross-functional teams.

Lead the migration of on-premise data warehouses to Snowflake, ensuring scalability and performance while mentoring a team and collaborating with stakeholders.

The Azure Data Engineer will manage data systems, develop SQL queries in Snowflake, and assist with cloud migrations and data governance.