Description

Design, build, and optimize scalable data pipelines and data models for high-volume datasets.

This role is remote.

Responsibilities

• Develop and maintain data models using Snowflake and dbt, writing complex SQL queries for large-scale processing.
• Create production-ready data workflows and ETL/ELT processes to ensure data quality and consistency.
• Support data validation, testing, reconciliation, and cleanup activities across the platform.
• Collaborate with risk, analytics, and business teams to support reporting and investment analytics initiatives.
• Assist with Power BI integration and dashboard support as needed.

Required Skills

• 5+ years of experience in large-scale data engineering and data warehousing.
• Strong proficiency with Snowflake, SQL, and dbt (Data Build Tool).
• Experience handling very large datasets and performance optimization.
• Python experience, including analytics libraries such as Pandas and NumPy.
• Proven track record with ETL/ELT pipeline development.
• Experience with data testing, validation, and data quality processes.

Preferred Skills

• Power BI development and support experience.
• Financial Services domain knowledge, specifically Investment Management or Asset Management.
• Exposure to investment risk analytics and cloud-based data platforms.

Key Skills

Education

Bachelor's degree