Good understanding of Data Warehousing and business intelligence concepts and testing techniques
Experience in Working with Star Schema, ODS, multi-dimensional models, slowly changing dimensions
Experience in working with ETL framework, Change Data capture, DataMart, Data models etc.
Working knowledge of test automation for backend using Java and associated frameworks
Experience in continuous testing practices in a CI/CD development pipeline, and deploying test automation
Solid experience in strategizing and planning all testing activities including automation.
Ability to review and analyze business requirements in order to produce test strategy and test cases.
Expertise working in Cloud data environment
Familiarity with one or more SQL-on-Hadoop technology (Hive, Impala, Spark SQL, Presto)
Experience in Agile projects (Scrum, Kanban etc.).
Working Knowledge in Test Management software (JIRA,qTest/ALM).
Solid experience with Defect Management Process.
Quick learner and self-starter who requires minimal supervision to excel in a dynamic environment.
Excellent analytical and problem solving skills.
Strong verbal and written communications skills.
Experience in Banking or Financial services domain is preferred.
Experience in working with financial platforms
Experience in Cluster, Containers/VMs, On Premise, On Cloud is preferred
Strong knowledge on Data Lake, Azure, ELT & ETL, Data Warehouse, BI, Data Factory Tools
Strong in SQL preparation in Oracle/SQL Server/NoSQL/RDMS/Big Data
Must have
Bachelor's degree in Computer Science or related field.
5 – 10 years of experience with Software Quality Assurance- QA project life cycle, test plan, test strategies, test scenarios, test cases, traceability matrix.
3 - 5+ years of experience in Database/Data Warehouse/ETL Testing.
3 - 5+ years of Strong experience in advanced SQL scripting.
Experience in MS SQL server, SSIS and SSRS.
3+ years’ experience of Data Lake/Hadoop platform implementation, including 3+ years of hands-on experience in implementation and performance tuning Hadoop/Spark implementations.
Awareness of Agile QA Software development life cycle –backlog, sprints, standups, burndowns.