Manager - Data Quality & Assurance

Location: Gurgaon

Experience: 3 – 8 years

Department: Technology

Level: Manager

About the Role

We are looking for a detail-oriented, execution-focused Data Quality & Assurance professional to ensure the reliability, consistency, and integrity of project and operational data across our climate and carbon programs. This role plays a critical part in building scalable QA processes, surfacing data risks early, and supporting accurate reporting and verification. You will own data quality across our Soil Organic Carbon (SOC), Alternate Wetting and Drying (AWD) for rice, biochar, and ARR portfolios, working across field measurements, lab soil results, remote sensing, and registry submissions.

Key Responsibilities

Data Quality & Validation

•     Perform quality checks and validation across multiple project datasets.

•     Identify inconsistencies, missing values, anomalies, and data integrity issues.

•     Establish monitoring mechanisms to improve overall data accuracy.

Process & Quality Management

•     Design and implement SOPs, quality frameworks, and control mechanisms.

•     Build repeatable QA workflows to improve operational efficiency.

•     Drive continuous-improvement initiatives across data collection and reporting.

Project & Cross-functional Collaboration

•     Partner with Operations, GIS, Product, and Project teams to resolve data issues.

•     Support teams in defining data standards and governance practices.

•     Coordinate with stakeholders to maintain timely, accurate reporting.

Audit, Compliance & Documentation

•     Maintain documentation and audit trails for quality reviews.

•     Support internal audits and external verification cycles with VVBs and registries such as Verra and Gold Standard.

•     Ensure readiness for reporting, certification, and quality assessments.

Reporting & Insights

•     Develop dashboards and quality metrics to track performance.

•     Generate periodic reports and recommend corrective actions.

What You'll Bring

•     3–8 years of experience in Data Quality, QA, Operations Excellence, Analytics, or related functions.

•     Strong attention to detail and structured problem-solving ability.

•     Experience working with large datasets and process management.

•     Comfortable with Excel / Google Sheets; familiarity with SQL, BI tools, or data platforms is a plus.

•     Experience creating SOPs, audit frameworks, and quality controls.

•     Ability to work across multiple teams and manage competing priorities.

Prior Experience working with carbon project developers, VVBs, or carbon registries is strongly preferred.

Good to Have

•    Experience in climate-tech, carbon markets, agriculture, geospatial, ESG, or impact sectors.

•    Exposure to verification, compliance, or MRV processes.

•    Knowledge of process-improvement methodologies.

How Success Is Measured

•     Reduction in data-quality issues and turnaround time.

•     Improvement in reporting accuracy and process compliance.

•     Strength of quality controls and audit readiness.

Excited to keep climate and carbon data honest We'd love to hear from you. Apply with your CV and a short note on a data quality problem you've solved.

Company Introduction : Prithu is a leading end-to-end carbon project developer, working with a goal of sequestering 20 million tonnes of CO2e by 2030. We help smallholder land stewards mitigate and adapt to climate change through the development and scaling of Nature Based Solutions (NBS).

Thousands of smallholder farmers form the core of our operations, implementing projects in regenerative agriculture, biochar, and afforestation, reforestation, and revegetation (ARR) across the Indian subcontinent. Our model ensures that land stewards receive the majority of project benefits, aligning incentives locally while strengthening the long-term sustainability of our projects.

We validate practice implementation, emissions, and removals through our state-of-the-art blockchain-based monitoring, reporting, and verification (MRV) system, powered by remote sensing, machine learning, and biogeochemical modelling, and calibrated using soil samples to accurately quantify and generate premium-quality carbon credits.