Specialist - Quality Engineering (Big Data)

TL;DR

Specialist - Quality Engineering (Big Data): Big data quality assurance and analytics with a specific focus on validating ETL processes and ensuring data accuracy using Google BigQuery and SQL. Focus on implementing GenAI for automated validation rules, anomaly detection, trend analysis, and building RAG-enabled frameworks for accurate AI outputs.

Company

hirify.global is a global IT services and consulting company specializing in technology solutions.

What you will do

• Validate big data ETL processes for accuracy and consistency across stages in GCP and AWS environments.
• Detect data discrepancies, troubleshoot issues, and maintain integrity in high-volume datasets.
• Automate QA tasks using Python, shell scripting, and data pipeline tools like Apache Beam, Dataflow, and Spark.
• Leverage GenAI (Claude mandatory) for data validation rules, reconciliation logic, anomaly detection, and root cause analysis.
• Build RAG-enabled support and Agentic AI frameworks for automated workflows and validation summaries.
• Validate BI reporting data using tools like Tableau and Looker.

Requirements

• 5 years of experience in QA with focus on big data quality assurance and analytics.
• Proficiency in Google BigQuery and SQL for data validation.
• Experience with ETL validation, cloud environments (GCP, AWS), and data ingestion/transformation/querying.
• Hands-on with data quality tools, monitoring frameworks, scripting (Python, Shell), Docker.
• Knowledge of Agile, JIRA, Confluence, BI tools (Tableau, Looker).
• Strong analytical and communication skills; background in media/entertainment and streaming analytics preferred.

Nice to have

• Familiarity with Agentic AI frameworks for metadata fetch and validation workflows.