Senior Data QA Architect

Data QA COE Development: Establish and lead the Data QA COE, document test standards and best practices across the program. Develop data quality testing frameworks, addressing key aspects such as data integrity, accuracy, completeness, timeliness, and consistency.

Manual & Automated Test Strategy: Design comprehensive test strategies, including both manual and automated testing, tailored for data pipelines, ETL/ELT processes, for on-prem and cloud data platforms.

Test Data Management: Manage and optimize test data management processes to support various testing requirements.

Data Quality Testing: Conduct comprehensive data quality testing to ensure data integrity, consistency, and accuracy. Implement data testing tools and frameworks such as dbt, and custom-built frameworks with java/Python for testing data pipelines and integrations.

Collaboration: Work closely with data engineers, analysts, and other stakeholders to identify quality requirements and ensure alignment. Partner with business and technical teams to align data testing initiatives with organizational goals and objectives.

Documentation: Maintain detailed documentation of QA processes, test cases, and defect tracking for continuous improvement. 

Test Data Management: Develop and oversee test data management strategies, including creating and maintaining reusable test data sets for multiple test scenarios.

Test planning:  Test requirement analysis, Test Estimation, Test Planning, support and mentor team to design test cases, traceability matrix, execution of test cases and support of Extract, Transform, Load (ETL/ELT) processes across multiple environments.

Client trusted Advisor: Serve as a strategic advisor to clients and stakeholders, providing expert recommendations on data quality assurance, governance, and testing best practices.

Build and Lead a High-Performing Team: Mentor, and manage a team of data QA engineers, fostering a collaborative and innovative work environment.

Innovation: Drive continuous improvement in testing processes by evaluating and adopting emerging technologies and best practices.

QUALIFICATIONS

• Deep understanding of data testing techniques, including data quality testing, data governance, data transformation validation, and end-to-end data flow testing.
• Strong experience in setting up data testing process, planning and managing testing between multiple environments
• Proficiency in automation tools and frameworks such as building custom frameworks in Java/Python, or equivalent, with specific experience in data testing tools like QuerySurge, DQ Analyzer, dbt, great Expectations or Informatica Data Quality.
• Strong experience in test data management.
• Extensive hands-on experience with testing data migrations, data transformations, data Analysis and data quality validations.
• Hands on experience in design and implementation of E2E Data testing strategies and developing data testing automation frameworks.
• Experience with Business Report Testing. Designing, testing, and troubleshooting data and reports.
• Deep understanding of data sources like Informatica, SQL Server, Oracle, Snowflake, Databricks,  and experience writing complex  SQL queries for data validation of business logic transformations
• Hands on experience with cloud data platforms like Snowflake, Databricks is a must. 
• Must have dataOps implementation experience, integrating QA automation suites with devOps pipelines
• Must have hands on Test automation experience to drive test automation strategy
• Good understanding or knowledge in Azure Cloud, GCP, ADF.
• Good exposure to Python, Pyspark, Databricks notebook
• Hands on experience with testing tools such as Great Expectations will be preferred
• Interact with project teams, development, operations, and infrastructure resources to recommend solutions to remediate data issues.
• Experience in defect life cycle management - logging, replication, triaging, verification, closing, metrics reporting, etc.
• Demonstrated ability to acquire high volumes of test data required to support Test execution.
• Good understanding of Agile methodology.
• Experience in summarizing large number of metrics into meaningful graphs and reports.
• Experience in client communications, sending status reports and addressing to client concerns in a timely manner