Sr. QA Analyst, Data & BI

Overview

The Sr. QA Analyst, Data & BI is responsible for overseeing quality assurance activities across Data and BI projects. This role involves leading test planning, execution, and reporting efforts, ensuring that data products meet quality standards and business requirements. You will collaborate with cross-functional teams, mentors QA analysts, and drives continuous improvement in testing processes and tools.

What We Offer:

• Salary: Competitive range of $75,000 - $100,000 per year.  This range reflects the budgeted compensation for this role.  The final offer will depend on experience, skills, and location.
• Bonus: This role offers a competitive bonus opportunity, awarded at the company's discretion and based on both overall business performance and your individual contributions.
• Tuition Waiver: Enjoy a tuition waiver after 6 months of employment for you AND your immediate family offered at UTI and Concorde campuses
• Paid Time Off: Competitive paid time off programs for employees (Vacation, Sick, Flexible)
• Retirement Matching: 50% match on the first 6% of your contributions after 90 days
• Paid Parental Leave: 4 weeks of paid leave for both birthing and non-birthing parents to bond with a new baby
• Competitive Insurance: Health, vision, and dental coverage for you and your dependents
• Pet Insurance: Competitive coverage for your furry family members through ASPCA

Responsibilities

• Lead Development of Data-Centric Test Strategies: Design and implement comprehensive test plans, test cases, and test scripts targeting data integrity across raw datasets, transformed outputs, and BI visualizations.
• Coordinate End-to-End Data Testing Activities: Oversee functional, regression, integration, and performance testing with a focus on validating data accuracy, consistency, and reliability throughout the data pipeline.
• Manage Data Defect Lifecycle: Utilize industry-standard tools to track, analyze, and resolve data-related defects, ensuring timely remediation and continuous quality improvement.
• Cross-Functional Collaboration: Partner with data engineering, analytics, product, and business teams to align on data quality objectives and ensure accurate representation of business metrics.
• Mentor QA Analysts in Data Validation Best Practices: Provide guidance on effective testing methodologies for data validation, including techniques for verifying calculations, transformations, and visualizations.
• Contribute to Automated Data Testing Frameworks: Support the design and implementation of automated testing solutions to streamline validation of data pipelines, BI dashboards, and reporting outputs.
• Ensure Compliance with Data Quality Standards: Enforce adherence to internal and external data governance policies, regulatory requirements, and industry best practices.
• Participate in Data Requirements and Design Reviews: Evaluate data models, transformation logic, and reporting specifications to identify potential quality risks and recommend improvements.
• Drive Continuous Improvement in QA Processes: Enhance data testing workflows, tools, and documentation to improve efficiency, coverage, and accuracy in data quality assurance efforts.
• Lead QA teams and manage multiple testing initiatives
• Adapt to changing project requirements and priorities
• Other duties as assigned

Qualifications

• Bachelor’s degree in a business or IT discipline, or equivalent work experience (required)
• Five (5) years of experience in data validation, quality assurance, and BI testing including leadership responsibilities (required)
• Strong proficiency in SQL for data validation and querying across large datasets
• Experience with BI tools (e.g., Power BI, Tableau, Looker) for testing dashboards and visualizations
• Familiarity with ETL processes and data transformation pipelines
• Understanding of data modeling and relational database concepts
• Strong analytical and problem-solving skills
• Strong analytical skills with attention to detail and a passion for data accuracy
• Experience with PowerShell preferred

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