What are the responsibilities and job description for the Data Engineer position at GP Fund Solutions?
– GP Fund Solutions
Where Data Meets Decision-Making. We turn numbers into insights that drive client success.
Join GP Fund Solutions (GPFS) - a people-first fund administrator serving clients across the US, UK, and EU. We offer a collaborative culture, real career growth, and benefits that invest in your future.
What You’ll Do:
Where Data Meets Decision-Making. We turn numbers into insights that drive client success.
Join GP Fund Solutions (GPFS) - a people-first fund administrator serving clients across the US, UK, and EU. We offer a collaborative culture, real career growth, and benefits that invest in your future.
What You’ll Do:
- 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.
- 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.