ETL QA

Design and execute test plans for ETL processes, ensuring data accuracy, completeness, and integrity.

Develop automated test scripts using Python or R for data validation and reconciliation.

Perform source-to-target data verification, transformation logic testing, and regression testing.

Collaborate with data engineers and analysts to understand business requirements and data flows.

Identify data anomalies and work with development teams to resolve issues.

Maintain test documentation, including test cases, test results, and defect logs.

Participate in performance testing and optimization of data pipelines.

Design and develop robust ETL pipelines using Python, PySpark, and GCP services.

Build and optimize data models and queries in BigQuery for analytics and reporting.

Ingest, transform, and load structured and semi-structured data from various sources.

Collaborate with data analysts, scientists, and business teams to understand data requirements.

Ensure data quality, integrity, and security across cloud-based data platforms.

Monitor and troubleshoot data workflows and performance issues.

Automate data validation and transformation processes using scripting and orchestration tools.

Required Skills & Qualifications

Hands-on experience with Google Cloud Platform (GCP), especially BigQuery.

Strong programming skills in Python and/or PySpark.

Experience in designing and implementing ETL workflows and data pipelines.

Proficiency in SQL and data modeling for analytics.

Familiarity with GCP services such as Cloud Storage, Dataflow, Pub/Sub, and Composer.

Understanding of data governance, security, and compliance in cloud environments.

Experience with version control (Git) and agile development practic