Job Description : Data Warehouse QA Analyst
Position : Data Warehouse QA Analyst
Contract : 6-month initial contract (potential for extension)
Location : Remote (Core hours : Central Time Zone 8-5)
Start Date : As soon as possible
About the Role : We are seeking a Data Warehouse QA Analyst to join our team supporting the residential and supply business.
You will be instrumental in testing data and analytical products within our data warehouse and data lake environments before they are released to production and business users.
Key Responsibilities :
- Design and develop test cases for data products in a data warehouse / lake environment.
- Perform manual testing to ensure industry standards are met.
- Prepare documentation, test plans, and test scripts.
- Validate data pipelines and dashboards in Google Cloud Platform (GCP) and AWS.
- Use SQL and Python to extract and validate data.
- Test dashboards built in Tableau and Power BI.
- Track and report defects using JIRA.
- Collaborate with data engineers, data analysts, and business analysts to ensure data accuracy and integrity.
- Participate in Agile methodologies, including two-week sprints and Scrum processes.
Technical Skills Required :
- Cloud Platforms : Proficiency in Google Cloud Platform (GCP) and AWS is mandatory.
- SQL and Python : Strong experience in writing SQL queries and using Python for data extraction.
- Testing Tools : Experience with JIRA for defect tracking and Agile project management.
- Data Visualization : Familiarity with Tableau and Power BI for testing dashboards.
- ERP Systems : Experience with Oracle ERP systems and data migrations is a plus.
Qualifications :
- Experience : 5-7 years of experience in data warehouse testing.
- Industry Knowledge : Understanding of data products, supply chain logistics, or manufacturing is beneficial but not required.
- Education : Relevant educational background in IT or related fields.
Interview Process :
- Round 1 : Initial screen (15-30 minutes) focusing on background and soft skills.
- Round 2 : Technical interview with data engineers, data analysts, and business analysts, including writing SQL queries and presenting solution designs.
Examples of Projects :
- Sales Team Support : Testing an analytical product that predicts customer churn based on sales trends and ensures that the algorithm’s outputs are accurate and actionable.
- Revenue Risk Analysis : Validating solutions that analyze revenue risk and supply chain disruptions, ensuring the data pipelines and products are built correctly.
Additional Information :
- This role focuses on validating data pipelines rather than building them.
- The team operates within an Agile methodology, and tasks are managed in JIRA.
- The data warehouse and lake environments are built on AWS and GCP, with source data in Oracle, IBM, and SQL Server ERPs.
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