Senior Snowflake Developer – Risk Technology (Contract)

ION Group•Jersey City, NJ

21h

About The Position

We are seeking a Senior Snowflake Developer to design, optimize, and enhance the Market Risk Time Series infrastructure built on Snowflake. This role requires deep expertise in Snowflake development, schema design, and performance tuning, combined with strong Python skills and domain knowledge in market risk. The candidate will work closely with the Market Data team and Risk stakeholders to ensure accurate, scalable, and auditable data solutions for VaR and SVaR calculations.

Requirements

7+ years of hands-on experience in developing applications using Relational Databases and Big-data platforms.
Snowflake Expertise
Strong experience in schema design, micro-partitioning, clustering, and query optimization.
Proficiency in Snowpark and stored procedures.
Expert-level SQL for complex queries and performance tuning.
Programming
Advanced Python for data engineering and integration.
Personal Attributes:
Strong analytical and problem-solving skills, including the ability to troubleshoot and resolve complex data related issues
Strong verbal and written communication skills
Self-starter and entrepreneurial in approach
Ability to escalate and follow-up proactively
Good time management skills

Responsibilities

Snowflake Development
Design and implement efficient and bi-temporal schemas leveraging micro-partitioning and clustering keys for optimal performance.
Develop and optimize SQL queries, stored procedures, and Snowpark-based transformations.
Implement query performance tuning and cost optimization strategies.
Data Engineering
Build and maintain Python-based ETL/ELT pipelines for sourcing historical market data from internal and external providers.
Integrate with quant libraries to identify data quality issues and validate risk inputs.
Data Quality & Remediation
Detect and remediate common data quality issues (gaps, stale data, outliers).
Implement algorithms for gap-filling, back-filling, and anomaly correction to ensure data is fit for VaR and SVaR calculations.