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QA Engineer with 1+ years in CRM Quality Assurance & Data Analytics
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Assessing your cultural and operational fit
Detail-oriented QA Engineer with 1.5+ years of experience in CRM Quality Assurance, functional testing, regression testing, workflow validation, and production release testing within the Australian solar industry. Experienced in independently handling end-to-end CRM QC processes, identifying critical defects, validating business workflows, and maintaining large-scale product databases for solar panels, inverters, and batteries. Strong analytical and problem-solving skills with hands-on experience in Python, SQL, Excel, and CRM operations.
St. Xavier's College, Ahmedabad
M.Sc. · Big Data Analytics
August 1, 2023 – June 30, 2025
Gujarat University (M.G. Science Institute), Ahmedabad
B.Sc. · Statistics
August 1, 2017 – June 30, 2020
Eclipse360
QA Engineer & Data Analyst
December 1, 2024 – Present
India
IBM
Data Analyst Intern
June 1, 2024 – August 1, 2024
India
CRM QA Testing & Product Validation
June 24, 2026 – Present
Performed end-to-end testing and validation for CRM workflows used in Australian solar operations.
Customer Acquisition Cost (CAC) Modeling
June 24, 2026 – Present
Developed predictive models using XGBoost and feature engineering techniques to estimate CAC for solar EPCs.
Machine Learning Certification
MentorNess
June 1, 2026 – Present
Data Analyst Certification
Unified Mentor
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including both QA testing and data modeling, shows a breadth of technical interest. The current role as 'QA Engineer & Data Analyst' aligns well with a target QA Engineer role, demonstrating a focused career path. The academic background in Big Data Analytics and Statistics, combined with certifications, indicates a commitment to continuous learning and skill development, which generally contributes to a positive cultural fit.
Soft Skills & Operational Fit
The candidate's experience indicates strong attention to detail, problem-solving abilities, and a proactive approach to quality assurance. The ability to independently handle QC processes and coordinate with developers suggests good operational fit for a QA role. The data analysis background also implies analytical thinking.