Data Engineer

• Own end-to-end delivery of data pipelines, models, and tests
• Implement reusable patterns and model structures in MSSQL, dbt Cloud, and Snowflake
• Monitor data quality, lineage, and job health
• Collaborate cross-functionally to define scalable data solutions
• Use data to drive decisions and support strategic growth objectives

Requirements

• Ideally would have 4-6 years of experience.
• Technical experience with Snowflake, Fivetran, dbt Cloud, MSSQL
• Ability to model data using best practices
• Proficiency in writing tests, implementing observability, and improving reliability
• Strong documentation and technical communication skills
• Hands-on experience using AI-assisted development tools (e.g., SQL/dbt copilots, LLMs for documentation, testing, or refactoring) to improve productivity and code quality
• Interest in learning and adopting emerging AI capabilities within the modern data stack

Core Competencies

Demonstrates expertise in end-to-end data pipeline delivery, leveraging tools like Snowflake and dbt Cloud to implement scalable data solutions. Proficient in data modeling, quality monitoring, and utilizing AI-assisted development tools to enhance productivity and code quality.

Highest-signal resume keywords

• Snowflake
• Dbt Cloud
• MSSQL
• Data Modeling
• AI-Assisted Development Tools

Hard Skills

• Data Pipeline Delivery
• Data Quality Monitoring
• Modeling Best Practices
• Writing Tests
• Implementing Observability

Soft Skills

• Technical Communication
• Documentation

Industry Keywords

• Data Solutions
• Strategic Growth Objectives
• Cross-Functional Collaboration

Tools & Technologies

• Fivetran
• SQL/dbt Copilots
• LLMs for Documentation
• Testing
• Refactoring