Data Engineer
Posted
Summary
Data engineer owning end-to-end delivery of data pipelines, models, and tests, building reusable patterns in MSSQL, dbt Cloud, and Snowflake while monitoring data quality and lineage. The role involves cross-functional collaboration and using AI-assisted development tools to boost productivity.
- 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