Qa Engineer

• Test Strategy & Design: Design, develop, and execute comprehensive test plans tailored specifically for data, analytics solutions, and data platform initiatives
• Pipeline Validation: Validate end-to-end data pipelines across all lifecycle stages including data ingestion, transformation, and ultimate reporting layers
• Core QA Testing: Perform thorough functional, regression, and rigorous data validation testing to confirm data accuracy and system stability
• Defect Management: Identify, document, track, and validate the resolution of defects utilizing structured QA methodologies
• Platform Sign-Off: Review data deliverables and provide formal QA sign-off for Snowflake and broader data platform releases to ensure production readiness
• Cross-Functional Collaboration: Partner closely with data engineers, business analysts, and analytics teams to root out data inconsistencies and ensure overall deliverable quality
• Release Management Support: Actively support scheduled release cycles, verifying the integrity of reporting outputs and downstream analytics

• Cloud Data Platforms: Proven experience working extensively with Snowflake data environments
• ETL & Data Pipelines: Strong background in data pipeline validation and ETL testing, particularly within Azure Data Factory (ADF)
• Data Streaming & Integrations: Familiarity with Kafka for real-time data streams and experience validating data across multiple interconnected sources
• Advanced Querying: Exceptional SQL skills for writing complex queries, data profiling, and deep-dive data reconciliation
• Specialized Tooling: Exposure to or familiarity with Cortex, Streamlit, and Salesforce Service Cloud (SFSC) is highly advantageous
• Professional Experience: Data QA Domain: Demonstrated experience in quality assurance and testing explicitly focused on data platforms, data warehouses, or analytics solutions
• Methodologies: Deep understanding of data validation techniques, regression testing, and data integrity methodologies (checking for accuracy, completeness, and consistency)
• Agile Frameworks: Experience operating smoothly within fast-paced, iterative Agile development environments
• Soft Skills: Outstanding attention to detail, highly developed analytical troubleshooting skills, and the ability to collaborate fluidly with engineering teams

Exposure to or familiarity with Cortex, Streamlit, and Salesforce Service Cloud (SFSC) is highly advantageous