Job Title: QA Engineer - Data/ETL

Experience Range: 7 - 12 years

Locations: Bangalore

Np: Immediate to 30 days

Industry: IT service management company

What you Will do
• Validates data and ETL pipelines to bring new data into a data
warehouse
• Collaborate 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 consistency
• Identify and research issues reported by internal and external
customers
• Manage defect resolution throughout the lifecycle and ensure issues
are resolved prior to production
• Develop and execute comprehensive data quality tests to identify
anomalies, inconsistencies, and data integrity issues for new product
development initiatives, product changes, policy changes, database
changes
• Data mining and detailed data analysis on data warehousing systems
• Create formal test plans to ensure the delivery of data related
projects involving applications that use ETL components
• Provide input and support big data testing initiative
• Define and track quality assurance metrics such as defects, defect
counts, test results, test status, test procedures
• Verify data accuracy, completeness, and consistency across various
data sources and pipelines
• Create and maintain test data sets for regression testing
• Provide test support for any issues that require code changes or
changes made directly to the ETL pipelines
• Implement and maintain automated testing framework for data
validation
• Continuously improve and expand test coverage through automation
• Develop and maintain testing scripts and tools to streamline the
testing process
• Collaborate with cross-teams to define data validation rules and
criteria
• Validate data transformations, aggregations, and calculations to
ensure accuracy and reliability
• Maintain comprehensive documentation of data quality issues and
resolutions
• Evaluate and transform documentation into test scripts as needed
• Work closely with cross-functional teams, including engineers, project
managers and other subject matter experts to understand data
requirements and validation needs
• Communicate effectively with stakeholders to report on data quality
findings and collaborate on improvements and identify gaps in test
coverage
• Schedule or attend peer reviews of test logic to ensure it has been
constructed correctly
• Communicate 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 failure
• Perform data testing on new and changed customer output files by
reviewing requirements, specifications, and technical design
documents and participating in design review meetings
• Create and support data validation scripts for new and existing ETL
pipeline changes
• Create visualization dashboards to analyze/monitor data for ETL
pipeline changes and flag any defects or anomalies in data from
regression data testing perspective
• Design, 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 equivalent
experience
• Proven experience as a QA Engineer with a focus data/ETL pipeline
testing, regression data testing
• Proven experience with one of BigData technologies such Pyspark,
Pandas, Spark, Hadoop, Hive
• Experience with creation/maintenance of data validation tools and
frameworks
• Proficient in Python as well as AWS tools
• Knowledge of data modeling concepts and ETL processes
• Familiarity with data integration and data warehousing technologies
such 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 problemsolving
aptitude.
• Strong organizational skills and ability to meticulously follow detailed
steps.
• Experience in creating robust test plans/strategies and test status for
Big Data product deliverables
• Excellent verbal and written communication skills.
• Willing and able to go above and beyond
• Ability to work collaboratively across different divisions.