Senior QA Analyst

November 21

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Zealogics Inc

WebsiteLinkedInAll Job Openings

IT consulting • Systems Implementation • IT & Engineering Staffing • Mechanical Engineering • Electronics Engineering

501 - 1000 employees

🏢 Enterprise

☁️ SaaS

🤖 Artificial Intelligence

Description

• Responsible for ensuring the quality and reliability of data engineering processes and systems. • Develop and implement comprehensive test plans and test cases for data engineering projects. • Create automated scripts in SQL/Python to validate data pipeline/transformations and generate reports. • Validate data for consistency, accuracy, and completeness from source systems to reports. • Execute test cases and analyze results to identify defects, inconsistencies, and areas for improvement. • Collaborate with data engineers, data scientists, and other stakeholders to ensure quality standards are met. • Participate in design and code reviews to provide input on quality and testability aspects. • Work closely with the development team to address defects in a timely manner. • Continuously improve testing processes and methodologies. • Provide guidance and mentorship to junior quality analysts. • Conduct functional, regression, performance, and load testing of DWH solutions. • Review Power BI reports and dashboards for specifications and data accuracy. • Document defects, issues, and improvements during testing and collaborate with the team.

Requirements

• 4+ years of experience • Bachelor's degree in computer science, engineering, or a related field. • Experience testing ADF Pipelines, Databricks Notebooks, and PBI reports/dashboards. • Proven experience as a Quality Analyst or similar role in data engineering or data analytics, preferably on Azure/Databricks environment. • Strong understanding of data engineering concepts, including data ingestion, transformation, and integration. • Proficiency in SQL and experience with data querying and analysis. • Proficiency in SQL and Python scripting for developing reusable scripts for test case execution. • Strong understanding of SQL queries, joins, and data manipulation techniques for data validation. • Experience writing Python scripts to automate test case execution and perform data validation. • Familiarity with testing frameworks and libraries in Python, such as pytest or unittest. • Knowledge of data validation techniques, including data profiling, comparisons, and quality checks. • Experience with testing tools and frameworks, such as PyTest. • Familiarity with version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) pipelines. • Excellent analytical and problem-solving skills. • Strong attention to detail and commitment to delivering high-quality results. • Excellent communication and collaboration skills. • Proven ability to work in a fast-paced, dynamic environment and manage multiple priorities.