Senior Consultant - W2 Only

Saransh Inc; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Saransh Inc in NYC is seeking a Senior Consultant to lead functional and automation testing for capital markets applications. You will validate index calculations, market data, and reference data while building robust automation frameworks in Java or Python to ensure quality and reliability.

The role involves regression, API, and end-to-end testing, data validation with SQL/ETL, and applying GenAI-assisted test design to boost QE productivity in a fast-paced financial environment.

Qualifications

• Functional and automation testing in Capital Markets.
• Experience validating index calculations and benchmark-related data.
• Automation frameworks using Java or Python and API testing.
• Data validation with SQL and ETL pipelines.

Responsibilities

• Perform functional and automation testing for Capital Markets.
• Validate index methodologies and benchmark-related data.
• Develop automation frameworks in Java or Python.
• Execute regression, API, and end-to-end tests.
• Validate data with SQL, ETL pipelines, and data services.
• Leverage AI tools to improve test design and QE productivity.
• Work with market data, pricing, and reference data.
• Experience with high-volume, low-latency financial data platforms is preferred.

Skills

Python

Java

SQL

GitHub Copilot

Job description

Job Title: Senior Consultant

Location: NYC, NY

W2 Position

Name

• Python
• GitHub Copilot
• Java
• SQL

Job Description/ Responsibilities/ Years Of Experience

• Perform functional and automation testing for Capital Markets ensuring quality, reliability, and performance.
• Understanding of index methodologies, benchmark indices, and capital markets data, experience in validating index calculations, market data, reference data, and benchmark-related financial applications or similar capital markets platforms
• Develop and maintain automation frameworks using Java or Python, and execute regression, API, and end-to-end testing.
• Validate data using SQL, databases, ETL pipelines, and Data Services to ensure data accuracy and integrity.
• Demonstrate AI fluency by leveraging AI-powered tools and Agentic AI/GenAI assistants to improve test design, test automation, defect analysis, root cause investigation, and overall QE productivity.
• Work with market data, pricing, reference data, index calculation, or similar financial applications.
• Experience testing high-volume, low-latency, real-time data platforms in Financial Services is highly preferred