Data Engineer

Role overview Develop and improve data warehouse structures and pipelines in Snowflake for business and analytical use cases. The work combines data modeling, advanced SQL, performance tuning, and practical use of generative AI tools, with regular coordination across internal teams and clients. This is a remote engagement expected to last at least six months.

Responsibilities - Design and optimize Snowflake data models, database objects, and pipeline workflows. - Write, debug, and tune complex SQL queries, views, stored procedures, and custom functions. - Use generative AI tools to assist with code improvements, query refactoring, script creation, and workflow automation. - Monitor virtual warehouse performance and improve query execution and micro-partition efficiency. - Translate business rules into data solutions in collaboration with clients and internal stakeholders.

Requirements - At least four years of data engineering experience, including data warehousing, schema design, and enterprise pipelines. - Advanced knowledge of Snowflake architecture and its stored procedures, views, functions, and performance optimization. - Strong SQL skills, including writing and tuning analytical queries and database scripts. - Hands-on experience using generative AI platforms to support development or process automation. - Strong written and spoken English for remote, client-facing collaboration.

Nice to have - Experience building automated ETL workflows with Alteryx. - Power BI experience, including dataset development, DAX, and reporting.

Benefits and work setup - Remote engagement of at least six months. - Compensation is based on experience and skill set.