ETL Quality Engineer

2 weeks ago

Bengaluru, Karnataka, India Manuh Technologies Full time

Key Responsibilities:

· Review and understand business requirements, data models, and ETL specifications.

· Design, develop, and execute ETL test plans, test cases, and test scripts.

· Perform data validation and data integrity checks from source to target systems (e.g., from databases, APIs, or flat files into data warehouses).

· Identify and document defects, inconsistencies, and data quality issues.

· Validate transformation logic in ETL processes (e.g., using SQL queries or scripts).

· Automate ETL test scenarios where applicable.

· Collaborate with data engineering and BI teams to resolve issues.

· Ensure data governance, privacy, and compliance rules are maintained during ETL processes.

· Perform regression, smoke, and system testing on data pipelines.

· Monitor scheduled ETL jobs and validate job success/failure outcomes.

· Understand business requirements and data flows to create comprehensive test plans and test cases for ETL jobs.

· Perform data validation and reconciliation between source systems, staging, and target data stores (DWH, data lakes)

· Collaborate with data engineering and BI teams to improve ETL processes and data pipelines.

· Maintain QA documentation and contribute to continuous process improvements.

· Creating Estimation, Test Plans, and Test cases for the Test stories under the sprint.

· Creating Test cases, Test data, execution, and capturing test results in Jira.

· Develop and execute automated and manual tests to ensure data accuracy and quality.

· Work with SQL queries to validate data transformations and detect anomalies.

· Initiate test results walkthroughs for the client to obtain UAT sign-off.

Must Have Skills:

· Strong SQL skills – ability to write complex queries for data validation and transformation testing.

· Hands-on experience in ETL testing – validating data pipelines, transformations, and data loads.

· Knowledge of data warehousing concepts – dimensions, facts, slowly changing dimensions (SCD), etc.

· ETL/Big Data Tools and Technologies: Azure Data Bricks, Azure DevOps, Azure Synapse Analytics.

· Defect Tracking tools: Jira, Bugzilla, Azure DevOps.

· understanding of data modeling, ETL workflows, and data architecture.

· Ability to analyze large data sets and identify discrepancies.

· Excellent problem-solving, communication, and analytical skills.

· Technical Skills: SQL, Hive, Azure Synapse, ADF, Oracle, Cosmos DB, Python basics.

· Experience in test case design, execution, and defect tracking.

· Experience with QA tools like JIRA, etc.

· Ability to work independently and collaboratively in an Agile/Scrum environment.

Good to Have Skills:

· Experience with ETL tools like Informatica, Talend, DataStage, or Azure/AWS/GCP native ETL services (e.g., Dataflow, Glue).

· Knowledge of automation frameworks using Python/Selenium/pytest or similar tools for data testing.

· Familiarity with cloud data platforms – Snowflake, BigQuery, Redshift, etc.

· Basic understanding of CI/CD pipelines and QA integration.

· Preferred experience for on-prem to cloud ETL testing.

· Exposure to data quality tools such as Great Expectations, Deequ, or DQ frameworks.

· Understanding of reporting/BI tools such as Power BI

Key Skills: Data Warehouse, ETL Testing, Datalake, SQL, Python, Snowflake.

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