Data Quality Test Engineer

Job Description
Title: Data Quality Test Engineer
Location: Manhattan, NY.
Work Mode: Hybrid 2 days/week onsite
Employment Type: Contract
Client: Automotive Mastermind Inc.
Mode of Interview: Skype + F2F

Recruiter screening priority

Google Cloud Platform E2E Data/Pipeline Testing API Testing Automation/UI Python + SQL/Database

If a candidate has strong Google Cloud Platform + E2E testing + API/UI automation, they are much closer to what this requirement is asking for than a candidate who is simply a strong traditional QA engineer.

Position Overview

We are looking for a strong Data Quality Engineer / Quality Engineer / SDET with hands-on experience testing cloud-based data platforms, applications, APIs, and end-to-end data pipelines.

The ideal candidate must have strong hands-on Google Cloud Platform experience and a solid background in UI and/or API testing, automation, data validation, and database testing.

This role requires genuine, hands-on experience working with Google Cloud Platform data environments and end-to-end testing. Candidates with only traditional QA experience and limited/no Google Cloud Platform exposure will not be considered.

Key Requirements

Strong hands-on Google Cloud Platform experience is mandatory.
Experience with end-to-end testing of Google Cloud Platform-based applications, data platforms, and pipelines.
Strong API testing and automation experience and/or strong UI testing/automation experience.
Strong overall QA/Test Automation/SDET background.
Hands-on experience with Python-based test automation.
Strong SQL and database/data-validation experience.
Experience testing data pipelines, ETL/ELT processes, batch and/or streaming data.
Strong understanding of data quality, data validation, reconciliation, accuracy, completeness, consistency, and integrity.

Key Responsibilities

Design and execute comprehensive testing strategies for Google Cloud Platform-based applications, data platforms, APIs, and data pipelines.
Perform end-to-end testing covering data ingestion, transformation, processing, storage, and downstream consumption.
Validate batch and streaming data pipelines for accuracy, completeness, consistency, and integrity.
Develop and maintain Python-based automation frameworks for API, backend, database, and data-validation testing.
Perform REST API testing, including functional, integration, regression, negative, and end-to-end testing.
Develop and execute UI automation tests using Playwright or similar frameworks.
Perform manual testing where required to validate application functionality and data flows.
Validate data across databases and data warehouses using SQL and automated data-quality checks.
Identify and troubleshoot data discrepancies, pipeline failures, API issues, and application defects.
Build automated reconciliation and validation checks to identify missing, duplicate, inconsistent, incorrect, or delayed data.
Test data across batch and streaming pipelines.
Integrate automated testing and quality checks into CI/CD pipelines.
Collaborate with Data Engineering, Development, DevOps, Product, and other technical teams to resolve quality issues.
Support data profiling, governance, lineage, and data-quality initiatives.
Google Cloud Platform Technologies

Strong hands-on experience with Google Cloud Platform is required. Experience with the following is highly preferred:

Google Cloud Platform (Google Cloud Platform) BigQuery Pub/Sub Google Cloud Storage (GCS) Dataflow Dataproc Cloud Composer Dataplex Testing & Automation