Senior Data Engineer

GP Fund Solutions; Latham (NY); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical, Dental & Vision Insurance

Company-Paid Life Insurance & 401(k)

Generous PTO & Paid Holidays

Hybrid Scheduling

Job summary

GP Fund Solutions is seeking a Senior Data Engineer to advance our data platform. You will design and maintain the data warehouse, transition towards a lakehouse, and optimize Snowflake workloads. Collaboration with analytics teams will shape data models and pipelines for decision-making.

You will implement dbt models, CI/CD practices, and robust data quality checks, supporting scalable analytics and AI/ML use cases. Hybrid work after probation and strong growth opportunities await.

Qualifications

• 5+ years of data engineering, analytics engineering, or related field.
• Strong Snowflake experience including SQL, access controls, and warehouse behavior.
• Proficiency with dbt, modeling, testing, and project structures.
• Solid data modeling knowledge including dimensional modeling and data marts.
• Experience building and optimizing data pipelines and ETL/ELT processes.
• Familiarity with Git-based workflows and CI/CD for data and cloud infra.

Responsibilities

• Develop and maintain data warehouse, transition to lakehouse.
• Evaluate Snowflake workloads for migration or optimization.
• Build dbt models across staging, intermediate, mart, and semantic layers.
• Create and maintain data pipelines ingesting data into Snowflake.
• Write optimized SQL for transformations and performance.

Skills

Snowflake

SQL

dbt

Data Modeling

ETL/ELT

CI/CD

Git

Data Pipelines

Cloud Infrastructure

Tools

Snowflake

dbt

SQL

Job description

Senior Data Engineer – 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:

• 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.

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

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