Data Engineer

• Assist with the development and maintenance of the core data warehouse structure and help with the transition to a lakehouse.
• Help evaluate existing Snowflake workloads and identify candidates for migration, optimization, or hybrid operation.
• Identify performance issues and assist with solution plans.
• Assist with the development and maintenance of dbt models across staging, intermediate, mart, and semantic layers, following established project structure, testing, and documentation standards.
• Help build and maintain data pipelines that ingest data from source systems into Snowflake, collaborating with platform and analytics teams on requirements and priorities.
• Write and optimize SQL transformations for performance, readability, and maintainability within Snowflake.
• Contribute to data quality and reliability efforts, including schema validation, source freshness checks, row-level testing, and pipeline monitoring.
• Participate in CI/CD processes for data, including automated testing, code review, and deployment practices using Git-based workflows.
• Contribute to Snowflake and cloud infrastructure configuration, including warehouse sizing, access patterns, and integration with surrounding services, under the guidance of senior engineers.
• Support orchestration workflows and data pipeline scheduling, helping ensure pipelines run reliably and recover gracefully from failures.
• Participate in design reviews, offering input on implementation approaches and learning from senior engineers’ architectural decisions.
• Troubleshoot and resolve pipeline and data quality issues, conduct root cause analysis and implement fixes.
• Document work clearly, including data models, pipelines, and operational runbooks, so the broader team can understand and maintain what you build.

• 3+ years of experience in data engineering, analytics engineering, or a closely related technical field.
• Hands-on experience with Snowflake, including writing performant SQL, understanding warehouse behavior, and working with Snowflake’s access and security model.
• Understanding of dimensional modeling, data marts, data quality controls, and enterprise reporting needs.
• Hands-on experience with dbt, including building and testing models, using macros, and following layered project structures.
• Solid understanding of data modeling concepts, including dimensional modeling and common transformation patterns.
• Proficiency in SQL for analytical and transformation workloads, including debugging and performance along with familiarity with common tools and practices used to do so.
• Experience with Git-based version control and collaborative development workflows.
• Familiarity with building or supporting data pipelines for analytics and/or AI/ML use cases.
• Exposure to CI/CD practices for data, cloud infrastructure, and orchestration tooling.

Pulled from the full job description

• Health insurance
• Paid time off
• Vision insurance
• Dental insurance
• Life insurance
• Paid holidays, * Strong training plans and materials provided.
• Competitive Medical, Dental & Vision Insurance.
• Company-Paid Life Insurance & 401(k).
• Generous PTO, Sick Time & Paid Holidays.
• Hybrid Scheduling after probation period.
• Inclusive, team-oriented culture where people come first.

At GPFS, every voice matters and every win is shared. We’re raising the bar in our industry-come grow with us!