Senior Software Quality Assurance Analyst
Senior QA Analyst ensures data quality and reliability for analytics products, defining KPIs, validating models, and using AI-assisted tools to improve analysis and reporting.
- Compensation
- Not disclosed
- Location
- ITA - Milan, Via Bisceglie
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Qa
- Posted
Skills
Must have
- Experience in data analysis, business intelligence, software quality assurance for data products or related roles.
- Strong analytical mindset and problem-solving skills.
- Good SQL skills and ability to explore, validate and interpret structured datasets.
- Experience with reporting, dashboarding or visualization tools, preferably Power BI.
- Ability to translate business needs into measurable KPIs, validation criteria and analytical specifications.
- Experience using AI-assisted tools to support analysis, validation, reporting, documentation or quality activities.
- Familiarity with specification-driven methodologies such as OpenSpec or equivalent approaches.
- Genuine interest in AI, analytics innovation and cutting-edge technology.
- Strong attention to detail and commitment to data quality, consistency and business value.
- Good communication skills and ability to explain insights and data issues to technical and non-technical stakeholders.
Full description
We are looking for a Senior Software Quality Assurance Analyst with a strong focus on Data & Analytics to ensure the quality, reliability and business value of data-centric products. The role will define and validate KPIs, benchmarks, analytical models, data quality rules, dashboards and reporting outputs, ensuring that users can trust the insights generated by the solutions.
The person will work at the intersection of business analysis, data validation and product quality. A key expectation is the use of AI-assisted tools and specification-driven practices to improve analysis, validation, documentation and acceptance criteria definition.
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Key Responsibilities
- Define, document and validate KPIs, metrics, benchmarking models and analytical requirements.
- Translate business questions into clear data requirements, quality criteria and acceptance conditions.
- Validate data quality, consistency, completeness and reliability across reporting and analytics outputs.
- Support the design and evolution of dashboards, reports, semantic models and analytical products.
- Analyze customer, supplier, financial, operational and market data to identify trends, gaps, opportunities and risks.
- Contribute to the definition of acceptance criteria and validation frameworks aligned with specification-driven delivery practices.
- Leverage AI-assisted tools to improve analysis, validation, documentation and quality processes.
- Support adoption of AI-enabled analytical and reporting capabilities where they improve clarity, productivity or business value.
- Create clear documentation of metrics, definitions, validation rules and expected analytical behaviours.
- Ensure analytics outputs are understandable, actionable and aligned with business stakeholder needs.
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Required Qualifications
- Experience in data analysis, business intelligence, software quality assurance for data products or related roles.
- Strong analytical mindset and problem-solving skills.
- Good SQL skills and ability to explore, validate and interpret structured datasets.
- Experience with reporting, dashboarding or visualization tools, preferably Power BI.
- Ability to translate business needs into measurable KPIs, validation criteria and analytical specifications.
- Experience using AI-assisted tools to support analysis, validation, reporting, documentation or quality activities.
- Familiarity with specification-driven methodologies such as OpenSpec or equivalent approaches.
- Genuine interest in AI, analytics innovation and cutting-edge technology.
- Strong attention to detail and commitment to data quality, consistency and business value.