Data Analysis QA Specialist

Job Summary

We are seeking a Data Analysis QA Specialist to audit, validate, and ensure the accuracy of all feedback analysis reports prepared by the data team. The candidate must understand performance marketing, real-estate lead funnels, and data analytics to identify errors, inconsistencies, and gaps in daily, weekly, and monthly analysis. The role is responsible for maintaining data quality, verifying insights, and ensuring error-free reporting for client teams and stakeholders.

Key Responsibilities

• Audit and validate feedback analysis reports prepared by the data analysis team.
• Recheck lead-stage classification (RNR, NT, Junk, QL, SV Proposed/Done, Booking).
• Identify data issues, missing values, incorrect formulas, or misaligned metrics.
• Verify daily lead delivery counts vs. feedback sheets, CRMs, and dashboards.
• Ensure consistency across Excel files, Python outputs, and automated reports.
• Check platform-wise/campaign-wise metrics for correctness and alignment.
• Detect anomalies, sudden drops/spikes, or inconsistencies in trends.
• Maintain standardized QC frameworks, checklists, and reporting templates.
• Coordinate with the data team to rectify errors and improve the accuracy of future reports.
• Work with marketing managers to verify if insights align with campaign expectations.
• Ensure timely QA sign-off before data is shared with clients or internal teams.

Required Skills

• Strong understanding of performance marketing metrics (Google, Meta, Taboola).
• Hands-on expertise in Excel (pivot, formulas, validation, QC frameworks).
• Good knowledge of Python-based outputs (basic understanding of Pandas preferred).
• Familiarity with data cleaning, deduplication, and lead funnel validation.
• Ability to analyse trends, spot inconsistencies, and identify root causes.
• Understanding of real estate buyer journey and feedback stages.

Qualifications

• Bachelor’s degree in Engineering/Maths/Statistics/Marketing/Analytics.
• Minimum 3 years of experience in data analysis, data QA, or marketing analytics.

Preferred Traits

• Highly detail-oriented with a zero-error mindset.
• Strong analytical thinking and documentation skills.
• Ability to challenge data, question assumptions, and validate accuracy.
• Comfortable working in fast-paced environments with tight deadlines.