Browse Jobs
Explore open roles across India.Explore active software roles. Sign up to apply and get AI match scores.
Top MatchesTop Job Matches
Loading jobs…
Back to Browse Jobs
NeuIQ
Data QA_Data Engineering_Jul 2026
NeuIQ
Mumbai•On-site•4-7 Yrs•2 days ago
Job description
Overview
We are seeking a detail-oriented Sr.
Responsibilities
- We are seeking a detail-oriented Sr. Data Quality Analyst to ensure the accuracy, consistency, and reliability of data products, dashboards, and AI-driven solutions. This role involves validating data pipelines, business logic, dashboard metrics, and AI-generated outputs using SQL and data validation techniques before delivery to clients.
- Data & Dashboard Validation
- Validate data accuracy across source systems, SQL queries, and reporting dashboards.
- Verify KPIs, calculated fields, filters, aggregations, and business logic.
- Perform reconciliation between source data and dashboard outputs.
- Conduct regression and sanity testing following data refreshes or model updates.
- AI Output Validation
- Validate AI-generated responses for accuracy, consistency, and business relevance.
- Identify hallucinations, incorrect calculations, and deviations from expected outputs.
- Create and execute test scenarios for AI agents and insight generation workflows.
- Support the maintenance of benchmark datasets for AI validation.
- Testing & Quality Assurance
- Develop and execute test plans, test cases, and validation checklists.
- Log, track, and verify defects through resolution.
- Support UAT activities and coordinate sign-offs with business stakeholders.
- Maintain QA documentation and testing evidence.
- Collaboration & Continuous Improvement
- Work closely with Data Engineers, AI Engineers, Business Analysts, and Project Managers.
- Recommend improvements to data quality, testing processes, and validation frameworks.
- Assist in automating repetitive validation tasks using SQL, Python, or other QA tools.
Qualifications
- 4-7 years of experience in Data QA, BI Testing, ETL Testing, or Analytics QA.
- Strong SQL skills for data validation and reconciliation.
- Understanding of data warehousing, ETL processes, and data quality principles.
- Exposure to AI/LLM-based applications is preferred.
- Prompt Evaluation, Data Quality Automation using SQL, Python
- Strong analytical, documentation, and communication skills.
- Strong attention to detail and analytical thinking.
- Ability to investigate and troubleshoot data discrepancies.
- Collaborative, proactive, and quality-focused.
- Comfortable working in Agile project environments.
- The ideal candidate is naturally curious about data, enjoys investigating discrepancies, and takes pride in ensuring every number, insight, and AI-generated response is accurate before it reaches the customer. You should be comfortable writing SQL, validating business logic, and collaborating across technical and business teams to maintain high-quality data products.