QA Engineer (Data Warehousing)

Enterprise Engineering Inc. (EEI); New York (NY); On-site; USD 90,000 - 120,000; Full time

Job summary

Enterprise Engineering Inc. (EEI) in New York, NY is seeking a QA Engineer for on-site testing with a NYC client. The role emphasizes manual regression testing and end-to-end validation of financial systems.

You will collaborate with developers, business analysts, and end-users to ensure quality across trading, reporting, and data processing platforms in a tight enterprise environment.

Qualifications

• Must have recent and extensive Investment Banking industry experience.
• Manual regression testing of financial reporting, reconciliation tools, and trading logic.
• Functional and integration testing across front-, middle-, and back-office systems.
• Negative and ad-hoc testing to assess resilience and error handling.
• UAT support: collaborate with developers, business analysts, and end-users on UAT guidelines.

Responsibilities

• Perform manual regression testing to ensure new deployments do not disrupt financial tooling.
• Conduct functional and integration testing across end-to-end trading and data flows.
• Execute negative and ad-hoc tests to uncover edge case failures.
• Support UAT by coordinating with stakeholders and validating acceptance criteria.

Skills

Investment Banking experience

Manual regression testing

Functional testing

Integration testing

Negative testing

UAT support

SQL queries

Unix/Linux

AWS

Java

SpringBoot

Jira

Bitbucket

Tools

Jira

Bitbucket

Job description

• Must have recent and extensive Investment Banking industry experience

QA Engineer

New York, NY

3 days a week onsite work

Onsite Interview Required

• Must have recent and extensive Investment Banking industry experience

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