Senior Data Engineer

GP Fund Solutions

$100K — $130K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in data engineering or closely related field.
  • Strong hands-on experience with Snowflake, including SQL writing and security model.
  • Understanding of dimensional modeling and enterprise reporting needs.
  • Expertise in dbt, including model building and testing.
  • Proficient in SQL for analytical workloads, with debugging skills.
  • Experience with Git-based version control workflows.
  • Familiarity with data pipelines for analytics or AI/ML use cases.

Responsibilities

  • Develop and maintain core data warehouse and transition to a lakehouse.
  • Evaluate and optimize existing Snowflake workloads for better performance.
  • Build and maintain dbt models adhering to project standards.
  • Create data pipelines that ingest from source systems to Snowflake.
  • Optimize SQL transformations for performance and readability.
  • Contribute to data quality efforts through validation and testing.
  • Engage in CI/CD processes including testing and deployment.

Benefits

  • Strong training plans and materials provided.
  • Competitive medical, dental, and vision insurance.
  • Company-paid life insurance and 401(k).
  • Generous PTO, sick time, and paid holidays.
  • Hybrid scheduling after probation period.
  • Inclusive, team-oriented culture.
Full Job Description
Senior Data Engineer- GP Fund Solutions

What You'll Do:
  • Develop and maintain core data warehouse structure and help with the transition to a lakehouse.
  • Evaluate existing Snowflake workloads and identify candidates for migration, optimization, or hybrid operation.
  • Develop and maintain dbt models across staging, intermediate, mart, and semantic layers, following established project structure, testing, and documentation standards.
  • 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.

What We're Looking For:
  • 5+ years of experience in data engineering, analytics engineering, or a closely related technical field.
  • Strong 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.
  • Strong 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.


Why GPFS?
  • 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.


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