**Role & seniority: ** QA Engineer (Traditional QA)

**Location & work type: ** New York, NY — 3 days/week onsite; onsite interview required

**Stack/tools (from reqs): **

AWS
Microservices, Spring Boot, Java
Streaming architecture
Databases (traditional + cloud) with strong SQL
Unix/Linux (backend navigation, commands/scripting)
Jira, Bitbucket (defect logging/sprint tracking/requirement mapping)

**Top 3 responsibilities: **

Manual regression testing to ensure releases don’t break financial reporting, reconciliation tools, or trading logic
Functional + integration testing across end-to-end transaction/trade lifecycles and data processing between front/middle/back office systems
Negative/ad-hoc testing (invalid data/unexpected actions) and UAT support in collaboration with developers, BAs, and end-users

**Must-have skills: **

Strong manual regression and end-to-end testing experience
Advanced SQL for financial data validation/integrity
Comfort with Unix/Linux for backend checks/scripting
Knowledge of financial/trading systems (e.g., reconciliations, trading logic, securities lending/equity swaps/FIX/T+1)
Solid defect tracking and requirements mapping in Jira/Bitbucket

**Nice-to-haves: **

Deeper familiarity with streaming systems and operational workflows in microservices on AWS
Broader exposure to addi

Full Description

QA Engineer

New York, NY

3 days a week onsite work

Onsite Interview Required

Client in NYC is looking for a Traditional QA Engineer.

Core Focus Areas

Manual Regression Testing: Verifying that new code deployments or updates do not break existing financial reporting, reconciliation tools, or trading logic.

Functional & Integration Testing: Validating the end-to-end flow of transactions, trade lifecycles, and data processing between front, middle, and back-office systems.

Negative & Ad-hoc Testing: Intentionally inputting invalid data or unexpected user actions to test application resilience and error-handling capabilities.

User Acceptance Testing (UAT) Support: Serving as a "quality catalyst " by collaborating directly with developers, business analysts, and end-users to manage UAT guidelines and verify real-world operational

Technical and Domain Competencies

Traditional QA teams handle highly complex enterprise systems and generally require a specific mix of financial and technical skills

Database & Data Integrity: High proficiency in writing complex SQL queries to manage and validate financial data stores. Traditional and Cloud Databases.

System Environments: Navigating backend servers using Unix/Linux commands and scripting.

Technology Stack: AWS, Microservices, SpringBoot, Java, Streaming Architecture

Domain Knowledge: Understanding specific financial structures such as Securities Lending, Equity Swaps, FIX protocols, and T+1 clearance mandates.

Tool Tracking: Rigorous defect logging, sprint tracking, and requirement mapping utilizing platforms like Jira and Bitbucket