ETL Testing

Job SummaryWe are looking for an experienced ETL Tester / Data QA Engineer with strong SQL skills to validate data pipelines, ETL processes, data transformations, and data quality across source and target systems. The candidate should have hands-on experience in writing complex SQL queries, performing data validation, and identifying data discrepancies.Key ResponsibilitiesPerform ETL testing for data extraction, transformation, and loading processes.Validate data between source and target systems.Write and execute complex SQL queries for data validation and reconciliation.Verify data transformations, mappings, joins, aggregations, and business rules.Perform data completeness, accuracy, consistency, integrity, and duplicate checks.Validate incremental and full data loads.Test ETL workflows, batch jobs, and data pipelines.Identify, document, and track defects using tools such as JIRA.Analyze production data issues and support root-cause analysis.Prepare test scenarios, test cases, test data, and execution reports.Work closely with developers, data engineers, business analysts, and other QA teams.Participate in regression, integration, system, and end-to-end testing.Required SkillsStrong hands-on experience in ETL/Data Warehouse Testing.Advanced SQL skills, including:JoinsSubqueriesCTEsWindow functionsAggregationsStored proceduresData reconciliationKnowledge of Data Warehousing concepts such as fact and dimension tables, star/snowflake schemas, and slowly changing dimensions (SCD).Experience with ETL tools such as Informatica, Talend, SSIS, DataStage, or similar.Experience with relational databases such as Oracle, SQL Server, PostgreSQL, or MySQL.Good understanding of SDLC/STLC and defect life cycle.Experience with Agile/Scrum methodologies.Good to HaveExperience with cloud data platforms such as Snowflake, AWS, Azure, or GCP.Knowledge of tools such as Databricks, Azure Data Factory, AWS Glue, or dbt.Experience with API testing or data pipeline automation.Basic knowledge of Python for test/data validation automation.Experience testing large-volume datasets and complex data migrations.QualificationsBachelor's degree in Computer Science, IT, Engineering, or a related field.Strong analytical and problem-solving skills.Good communication and documentation skills.