Our client is the leading retail chain in Uzbekistan, with about a million regular customers and more than 125 stores in 11 regions. The company operates supermarkets, neighborhood stores, convenience stores, a wholesale store, and an online supermarket. The client also runs two warehouses (dry and temperature-controlled) and a fruits/vegetables hub.

Project Objectives:

The client wants to replace the obsolete DWH solution based on SAP BW and deploy a robust, flexible, and scalable analytical cloud platform based on the cutting edge technology stack. This project will enhance data quality and governance practices and support significant company growth, laying the groundwork for advanced AI/ML solutions.

Responsibilities:

• Develop and execute detailed test plans, test cases, and test scripts for data validation, ETL processes, and data-related workflows.
• Establish, enforce and improve data quality standards and guidelines to ensure compliance and consistency across datasets.
• Perform thorough manual testing of data transformation workflows to ensure they meet the specified requirements and quality standards.
• Identify, document, and track defects using issue tracking tools.
• Collaborate with Data Engineers, DevOps, and business teams to understand the system requirements and business needs.
• Conduct data validation and integration testing.
• Review and analyze system specifications and requirements to identify potential data-related issues.
• Verify the accuracy, consistency, and completeness of data by performing data validation and integrity checks. Identify and rectify discrepancies or anomalies.
• Design and document test cases and test scenarios tailored for data validation, ETL processes, data migration, and other data-related workflows.
• Analyze data profiles to understand data structures, patterns, and anomalies for effective quality assessment.
• Perform various types of testing, including functional testing, regression testing, integration testing, and performance testing, on data pipelines, ETL workflows, and data transformations.
• Investigate and perform root cause analysis of data-related issues, collaborating with relevant teams to determine underlying causes and implement effective solutions.
• Stay updated with the latest trends, tools, and best practices in test automation and quality assurance.
• Suggest and implement improvements to the QA process and methodologies.
• Provide clear and concise test summary reports to stakeholders.
• Participate in requirement and design review meetings to give feedback from a QA perspective.
• Mentor junior QA engineers and provide guidance on testing best practices.

Requirements:

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• Proven experience (5+ years) as a QA Engineer with a strong focus on manual testing.
• Solid understanding of the software development lifecycle (SDLC) and QA methodologies.
• Strong experience with issue tracking tools such as Jira, Bugzilla, or similar.
• Excellent analytical and problem-solving skills.
• Detail-oriented with strong organizational and documentation skills.
• Ability to work effectively within an Agile/Scrum environment.
• Ability to collaborate effectively with cross-functional teams and stakeholders.
• Knowledge of data quality frameworks, data profiling, data validation, and data cleansing techniques.
• Familiarity with data governance principles and best practices.
• Experience in developing and executing test plans, test cases, and test scripts specific to data quality assurance.
• Understanding of database systems and ETL (Extract, Transform, Load) processes.
• Proficiency in working with relational databases (SQL, MySQL, PostgreSQL, etc.)
• Ability to create comprehensive documentation of data quality processes, standards, and issues.
• Upper-Intermediate level of English.
• Experience in the retail sector.

Nice to Have:

• Experience with BI tools (e.g., Tableau, Power BI) and data warehouse testing.
• Familiarity with SQL and database testing.
• Understanding of basic automation testing principles.