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QA Engineer ETL/Data

3 months ago


Bengaluru, India Antal International Full time
Position Title: QA Engineer - DataAbout the team: You will be part of the Inscape QA team that is focused on quality on front end embedded client/TV as well as backend cloud services that reports high quality data to customers.

The backend QA team is responsible to validate our award-winning Inscape data set which is used by millions of people every day. We have top-notch software engineers, but with this much data, occasionally, there are errors. That’s where you come in We’re looking for detail-oriented testers to use our QA team that validates the Inscape data and alert us of critical bugs and errors before actual users are affectedWhat you Will do Validates data and ETL pipelines to bring new data into a data warehouseCollaborate with cross-functional teams (Product/Data science/Data engineering) to develop, execute, and automate data testing processes, ensuring that our data assets meet the highest standards of accuracy, completeness, and consistencyIdentify and research issues reported by internal and external customersManage defect resolution throughout the lifecycle and ensure issues are resolved prior to productionDevelop and execute comprehensive data quality tests to identify anomalies, inconsistencies, and data integrity issues for new product development initiatives, product changes, policy changes, database changesData mining and detailed data analysis on data warehousing systems Create formal test plans to ensure the delivery of data relatedprojects involving applications that use ETL components Provide input and support big data testing initiative Define and track quality assurance metrics such as defects, defectcounts, test results, test status, test procedures Verify data accuracy, completeness, and consistency across variousdata sources and pipelines Create and maintain test data sets for regression testingProvide test support for any issues that require code changes or changes made directly to the ETL pipelinesImplement and maintain automated testing framework for data validationContinuously improve and expand test coverage through automation Develop and maintain testing scripts and tools to streamline thetesting process Collaborate with cross-teams to define data validation rules andcriteria Validate data transformations, aggregations, and calculations toensure accuracy and reliability Maintain comprehensive documentation of data quality issues andresolutions Evaluate and transform documentation into test scripts as needed Work closely with cross-functional teams, including engineers, projectmanagers and other subject matter experts to understand data requirements and validation needsCommunicate effectively with stakeholders to report on data quality findings and collaborate on improvements and identify gaps in test coverageSchedule or attend peer reviews of test logic to ensure it has been constructed correctlyCommunicate with subject matter experts to research source of issues and proposed resolutions, as well as, loading and examining data, business rules, and editorial policy to determine point of failurePerform data testing on new and changed customer output files by reviewing requirements, specifications, and technical design documents and participating in design review meetingsCreate and support data validation scripts for new and existing ETL pipeline changesCreate visualization dashboards to analyze/monitor data for ETL pipeline changes and flag any defects or anomalies in data from regression data testing perspectiveDesign, develop, automation tools to test ETL pipelines Write Python scripts in PySpark for data processing and manipulation About you: 2+ years of proven experience in software engineering Bachelor’s degree in Computer Science, Engineering, or equivalentexperience Proven experience as a QA Engineer with a focus data/ETL pipelinetesting, regression data testing Proven experience with one of BigData technologies such Pyspark,Pandas, Spark, Hadoop, Hive Experience with creation/maintenance of data validation tools andframeworks Proficient in Python as well as AWS tools Knowledge of data modeling concepts and ETL processes Familiarity with data integration and data warehousing technologiessuch as Databricks/Snowflake Experience with system integration testing, end-to-end testing,databases, CI/CD pipelines Ability to document and troubleshoot errors. Strong attention to detail and patience to track down difficult issues. Possessing an analytical mind, critical-thinking skills, and problem-solving aptitude. Strong organizational skills and ability to meticulously follow detailedsteps. Experience in creating robust test plans/strategies and test status forBig Data product deliverables Excellent verbal and written communication skills. Willing and able to go above and beyond Ability to work collaboratively across different divisions.

. Skillset Required: Integration Testing,

Analytical Mind,

Written Communication Skill,

Written Communication,

Quality Assurance,

Big Data,

Data Analysis,

Visio,

Regression Testing,

Attention To Detail,

Oop,

Data Modeling,

Panda,

Embedded C,

Test Plans,

Organizational Skills,

Python,

Bigdata,

Excel,

Communication Skill,

Organizational Skill,

Patience,

Hadoop,

Detail-oriented,

Documentation,

Data Mining,

Data Integration,

Strong Attention,

Cloud Services