Senior Data Engineer - Snowflake

Concord USA•Open to multiple locations in the US, MN

9h•Remote

About The Position

We are seeking a resourceful, self-directed Snowflake Data Engineer to join a high-performing team supporting enterprise data initiatives. This is a hands-on pipeline development role for someone who thrives on digging in, solving problems independently, and leveraging the latest AI-assisted development tools, including Snowflake Cortex, to build and reverse-engineer complex data products. The ideal candidate is as comfortable reading and reverse-engineering existing data products as they are building new ones.

Requirements

Proven experience with Snowflake data pipeline development (ingestion, transformation, orchestration).
Hands-on experience using LLM-assisted development tools for coding, debugging, and solution design.
Familiarity with Snowflake Cortex Code or comparable AI coding/code generation platforms.
Ability to read, analyze, and reverse-engineer existing data products and queries.
Strong SQL skills; experience with Snowpark, dbt, or Python a plus.
Excellent written and verbal communication skills — comfortable presenting ideas to both technical and non-technical audiences.
Demonstrated accountability: owns outcomes, follows through, and escalates appropriately.
Must be authorized to work legally in the US without sponsorship, now or in the future.

Nice To Haves

Direct experience with Snowflake Cortex for AI-assisted development and code generation.
Exposure to Snowflake Intelligence or similar intelligent data platform features.
Experience integrating or building with ML and analytical models within Snowflake.
Background in IT consulting or client-facing staffing engagements.
SnowPro certification (Core or Advanced: Data Engineer) a plus.

Responsibilities

Design, build, and maintain Snowflake data pipelines in a fast-paced consulting environment.
Reverse-engineer existing data products and architectures to accelerate development.
Apply Snowflake Cortex, Snowflake Intelligence, or equivalent LLM/AI coding tools in daily development workflows.
Leverage ML and analytical models to enhance data solutions and deliver business insights.
Collaborate closely with internal teams and direct client stakeholders — communicating progress, blockers, and ideas clearly.
Independently troubleshoot issues and propose solutions without requiring step-by-step direction.
Document pipelines, decisions, and processes to support knowledge transfer and team continuity.