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🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
TeizoSoft Private Limited • Gurugram, Haryana, India
Role & seniority: Data QA / ETL Testing Engineer (seniority not specified)
Stack/tools: SQL (complex joins, procedures, window functions, aggregations); RDBMS (SQL Server, PostgreSQL, Oracle) and/or NoSQL; ETL tools (Informatica, Talend, SSIS, ADF or similar); Python/PyTest; data warehousing concepts (star/snowflake, fact/dim); cloud platforms (AWS, Azure, GCP); CI/CD tools (Jenkins, GitLab CI, Azure DevOps); API testing tools (Postman, Swagger)
Develop/execute test strategies, plans, and cases for data pipelines, ETL/ELT processes, and analytical systems
Validate data transformations, mappings, business rules, quality checks, and end-to-end data lineage
Build/maintain automated data validation scripts; perform data ingestion/processing/storage tests; CI/CD integration; defect management
Strong SQL proficiency (complex joins, procedures, window functions, aggregations)
Experience validating large datasets across RDBMS and/or NoSQL
ETL testing experience with Informatica, Talend, SSIS, ADF or similar
Automated test scripting in Python (PyTest or similar)
Data warehousing concepts and cloud data pipelines; CI/CD and API testing
Ability to analyze defects, provide root-cause analysis, and document results
Experience with data governance, security, and privacy standards
Experience testing data services/microservices; familiarity with data quality frameworks
Location
Key Responsibilities
Develop and execute comprehensive test strategies, test plans, and test cases for data pipelines, ETL processes, and analytical systems. Validate data transformations, data mapping, and business rules across multiple data sources. Perform in-depth data quality checks, including completeness, accuracy, consistency, and integrity. Conduct ETL/ELT testing, including source-to-target validation, schema verification, and data reconciliation. Work closely with Data Engineers, Developers, and Analysts to understand requirements and ensure end-to-end data accuracy. Build and maintain automated data validation scripts and frameworks using SQL, Python, or other relevant tools. Test data ingestion, data processing, and data storage across relational and non-relational databases. Identify data defects, provide root-cause analysis, and ensure timely resolution. Validate performance, scalability, and reliability aspects of data flows and pipelines. Work within CI/CD environments to integrate data testing into automated pipelines. Document test results, defect logs, and data quality metrics. Ensure compliance with data governance, security, and privacy standards.
Technical Skills
Strong hands-on experience with SQL (complex joins, stored procedures, window functions, aggregations). Experience in validating large datasets across RDBMS (e.g., SQL Server, PostgreSQL, Oracle) and/or NoSQL systems. Experience with ETL testing using tools such as Informatica, Talend, SSIS, ADF, or similar. Hands-on experience in writing automated test scripts using Python, PyTest, or similar frameworks. Familiarity with data warehousing concepts, star/snowflake schemas, fact/dimension tables. Understanding of data pipelines on cloud platforms (AWS, Azure, or GCP). Experience with CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, etc. Ability to test APIs, data services, and microservices using tools like Postman, Swagger, or automation frameworks.
Soft Skills & Behavioral Competencies
Strong analytical and logical reasoning skills. Excellent attention to detail and commitment to data accuracy. Ability to collaborate effectively across cross-functional teams. Clear and concise communication skills (written & verbal). Strong documentation and reporting skills. Ability to work independently and drive tasks to completion.
Education: Bachelors or Masters degree in Computer Science, Information Technology, Data Engineering, or a related field.
(ref: hirist.tech) Show more Show less