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A715-Quality Assurance Tester (805255)

Fellowship Health Resources, Inc.

7h ago

0DevTrenton, NJ, USjobspy_indeed
remoteindeed

Job Description

**Both Phone and In Person** **Note: This is a Hybrid position \- 3 Days On\-Site, 2 Days Remote. Projected Project End Date: 09/30/2027** **Our direct client has an opening for a Quality Assurance Tester (805255\)** **This position is for up to 12 months, with the option of extension, and is located in Trenton, NJ 08625** **We can work corp to corp or W2\. Send rate and resume** **If you are interested, please submit the following:** **YOUR CURRENT RESUME** **YOUR HOURLY RATE** **Data / QA Automation Experience Required 7 Years** **Advanced SQL Querying Required 7 Years** **Manual Backend / Data Validation Required 7 Years** **AWS Core Cloud Services Required 3 Years** **Snowflake (or competitor like Databrick/BigQuery/Reshift) Required 3 Years** **dbt (data build tool) Validation Highly desired 2 Years** **Salesforce Data Integration Highly desired 3 Years** **Copado Robotic Testing Desired 1 Years** **You will own data quality and regression testing for our cloud data platform, ensuring seamless data flow and transactional consistency from our source systems into our data warehouse. This role requires a balance of building automated checks and performing hands\-on manual data reconciliation to quickly isolate anomalies.** **Build and maintain scalable test automation frameworks while performing strategic manual data validation across cloud data pipelines.** **Write complex, high\-performance SQL queries for deep\-dive data reconciliation, schema validation, and end\-to\-end data integrity checks.** **Validate transactional consistency and data object mapping between Salesforce and downstream data platforms.** **Utilize automated testing tools to support Salesforce environments, with experience in Copado Robotic Testing considered a major plus.** **Integrate automated quality gates and data tests directly into DevOps and CI/CD deployment pipelines.** **Collaborate closely with data engineering and cloud architecture teams to troubleshoot and resolve pipeline anomalies.**