Data Quality Engineer - Big Data,.NET, GCP BigQuery

Role: Data QE / Functional QE

Experience Required: 6–8 Years

Primary Skills: Big Data & Hadoop Ecosystem,.NET Technologies, Agile Way of Working, Functional Testing

Role Overview

We are seeking a versatile Quality Engineer with strong experience across both Functional Testing and Data/Big Data QE disciplines. The ideal candidate brings deep technical knowledge in.NET development, SQL, Big Data platforms, and data validation frameworks. This role supports testing across application functionality, large-scale data processing, and cloud-based systems.

You will work closely with developers, analysts, and business stakeholders to validate system behavior, ensure data integrity, and deliver high‑quality, scalable, and secure solutions.

Key Responsibilities:

Functional QE Responsibilities

Develop a thorough understanding of the product from functional and technical perspectives.

Participate in all phases of development to validate functional behavior, performance, integration, and business logic.

Work closely with business analysts to understand change impacts on existing processes.

Design, implement, and execute functional and regression test cases.

Validate web applications, APIs, UI behavior, and cross-browser compatibility.

Write and maintain unit-level test cases as needed to support development teams.

Analyze logs, trace flows, and use diagnostic tools to troubleshoot issues.

Contribute to design documentation and knowledge-sharing materials.

Participate in Agile ceremonies and sprint planning activities.

Mentor junior testers and collaborate with cross-functional technical teams.

Data QE / Big Data Responsibilities

Perform end‑to‑end data validation for large-scale data pipelines in Big Data and Hadoop ecosystem environments.

Conduct ETL testing, DB testing, data migration validation, and reporting validations.

Work with GCP BigQuery, Python, and PySpark to support data processing and test automation.

Analyze and validate complex datasets across multiple sources and formats.

Write and optimize complex SQL queries for data validation, reconciliation, and anomaly identification.

Support Big Data initiatives with a strong focus on data quality, accuracy, and completeness.

Ensure all transformations, aggregations, and business rules are implemented correctly.

Participate in large data-platform projects, including PC Insurance-related data initiatives.

Essential Skills & Experience:

.NET / Functional QE Skills

Strong technical skills with C#, ASP.NET, ASP.NET Core, and Web API development.

Experience with front-end technologies: HTML, CSS, JavaScript, jQuery, JSON.

Solid knowledge of SQL Server (T‑SQL, SSRS, and database administration fundamentals).

Hands-on experience with Entity Framework and LINQ.

Experience developing or validating secure web applications using secure coding principles.

Ability to write clean, readable, maintainable code and adhere to coding standards.

Strong understanding of OO concepts, design patterns, and software design principles.

Experience with cross-browser rendering and performance considerations.

Strong background in writing and maintaining unit tests.

Experience using .NET diagnostic tools to profile and investigate performance issues.

Data QE / Big Data Skills

6–8 years of overall QE experience with 3–4 years in Data Testing.

Strong experience with Big Data / Hadoop ecosystem technologies.

Hands-on experience with GCP BigQuery, Python, and PySpark.

Experience with ETL testing, data migration, and report validation.

Expert-level ability to write and interpret complex SQL queries.

Experience validating large datasets and distributed data pipelines.

Desirable / Nice-to-Have Skills:

VB.NET experience.

Experience with Knockout.js.

Experience with WF, WCF, and WPF.

Previous experience in PC Insurance data ecosystem is a strong asset.

Exposure to modern data platforms and cloud ETL frameworks.