QA Engineer Data - (IN) at IT Scout

⚠️Only available for #residents of #Mexico⚠️

About team:
You will be part of the Inscape QA team that focuses on quality on front-end embedded client/TV and backend cloud services that report high-quality data to customers. The client QA team tests various embedded clients and firmware for various Vizio TVs. Thebackend QA team is responsible for validating our award-winning Inscape data set, which millions of people use daily. 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 alerts us of critical bugs and errors before users are affected.

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 accuracy, completeness, and consistency standards.
🔸Identify and research issues reported by internal and external customers.
🔸Manage defect resolution throughout the lifecycle and ensure issues are resolved before 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, and 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 significant data testing initiatives.
🔸Define and track quality assurance metrics such as defects, defect counts, test results, status, and 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 issues requiring code changes or changes made directly to the ETL pipelines.
🔸Implement and maintain an 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, 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 a 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 focus data/ETL pipeline testing and regression data testing.

· Proven experience with BigData technologies such as Pyspark, Pandas, Spark, Hadoop, and Hive.

· Experience with the creation/maintenance of data validation tools and frameworks • Proficient in Python and AWS tools.

· Knowledge of data modeling concepts and ETL processes.

· Familiarity with data integration and warehousing technologies like 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 complex issues.

· Possessing an analytical mind, critical-thinking skills, and problem solving 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.

What We Offer:

• Budget 80K per year + Perks
• Flexible Work Environment
• Responsible Paid Time Off Policy
• Work from home for better life/work balance