Senior QA Engineer (ETL & Data Engineering)

Remote

Job Requirements

Experience

8 - 10 years

Primary Skills

- QA engineering
- ETL/data testing
- SQL & advanced SQL
- Snowflake

Key Responsibilities

QA Strategy & Test Execution

Design, plan, and execute comprehensive test strategies for data pipelines, ETL workflows, and cloud-based data platforms.

Validate data integration, data transformation logic, data quality, and data reconciliation across multiple layers.

Collaborate with Data Engineers, Architects, and Product Managers to ensure functional and non-functional requirements are testable and well-defined.

ETL & Data Pipeline Testing

Perform ETL validation across staging, raw, refined, and curated zones using Medallion Architecture principles.

Validate data mappings, data models, data lineage, and transformation logic.

Ensure data completeness, accuracy, timeliness, and consistency across systems.

SQL & Advanced SQL

Write complex and optimized SQL queries to test data pipelines and transformations.

Perform data profiling, data sampling, and reconciliation using SQL.

Validate data against business rules and aggregation logic.

Snowflake & Cloud Data Platforms

Test data workflows built on Snowflake SaaS platform.

Validate Snowflake objects—tables, schemas, views, tasks, stages, and stored procedures.

Understand and test pipelines built with Medallion Architecture / multi-zone architecture.

Automation & Toolin





Build and maintain ETL test automation frameworks using Python or other scripting languages.

Automate data validation, schema checks, reconciliation, and API validations.

Perform API testing (manual and automated) using Python scripts or tools like Postman.

AI in Testing

Explore and integrate AI/ML-based techniques to accelerate ETL testing (e.g., anomaly detection, metadata-driven test generation).

Contribute to long-term strategy for AI-driven test automation and intelligent data quality monitoring.

Quality Governance

Establish and enforce QA processes & best practices.

Use test management and defect-tracking tools efficiently.

Ensure timely reporting of test progress, risks, and quality metrics.

Test Management & Defect Management

Work extensively with tools like JIRA, Azure DevOps, or similar for:

Test case management

Test cycle execution

Defect logging, tracking, and triaging

Sprint-level QA planning and reporting

Required Skills & Qualifications

7+ years of experience in QA engineering with strong focus on ETL/data testing.

Proficiency in SQL & advanced SQL for data validation in large datasets.

Solid understanding of data engineering principles and modern data architectures.

Hands-on experience with Snowflake or similar cloud data warehouses.

Experience with medallion/batch-layered architectures (Bronze–Silver–Gold).

Experience with ETL test automation using Python or frameworks like PyTest.

API testing experience (manual + Python-based automation).

📌 QA Engineer (ETL & (Uttar Pradesh)
🏢 Sparix Global
📍 Uttar Pradesh