Data Engineer with ~2 years experience in ETL pipelines and AI automation
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Engineer with ~2 years of experience building ETL pipelines, automation systems, and data processing workflows using Python, SQL, and AWS. Skilled in handling structured datasets and developing scalable solutions for analytics and operational use cases. Strong exposure to LLM-based automation and cloud-native architectures. Focused on building efficient, reliable, and production-ready data systems.
Dhirubhai Ambani University, Gandhinagar
M.Sc. · Data Science
N/A – June 30, 2024
GLS University, Ahmedabad
B.Sc. · Information & Technology
N/A – June 30, 2022
GrowExx
Data Engineer
January 1, 2024 – October 1, 2025
India
Supply Chain Audit Automation
June 13, 2026 – Present
Built a data processing system handling 100,000+ records, identifying missing and inconsistent transactions. Leveraged Airflow to automate data migration workflows from AWS RDS to Snowflake, ensuring reliable and scalable data availability for downstream analysis. Developed Power BI dashboards, reducing manual audit time by 50–60% and improving decision-making.
Intelligent Call Scheduling System (POC)
June 13, 2026 – Present
Designed an automated scheduling system using Google Calendar API and LLMs. Built logic to analyse availability and identify optimal meeting slots across multiple participants. Implemented conflict detection and free-busy validation, eliminating manual coordination efforts.
AI-Driven Recruitment Orchestration
June 13, 2026 – Present
Developed automation workflows using Python and LLMs to streamline candidate screening and scheduling processes. Processed and managed recruitment data on AWS (EC2, Lambda, S3), ensuring scalable and reliable data availability for downstream workflows. Designed Python-based data pipelines to ingest and process recruitment data, integrating LLMs for job description generation, skill mapping, insights generation, and candidate scoring.
Cultural Fit Analysis
The candidate's projects demonstrate a diverse application of data engineering skills, including supply chain, recruitment, and scheduling automation, which indicates adaptability and a broad interest in solving different business problems. The use of various technologies (AWS, Azure, Snowflake, Airflow, LLMs) suggests a willingness to learn and apply new tools. The target role of Data Engineer aligns well with the candidate's experience and stated skills. The low psychometric test score, however, could be a flag for cultural fit, depending on the specific organizational values related to teamwork and attitude.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to automate complex processes and improve efficiency, suggesting a problem-solving mindset and a focus on operational improvements. Collaboration with cross-functional teams is also mentioned, indicating teamwork skills. However, the psychometric test score is low (218/500), which might raise concerns regarding logical reasoning, work attitude, stress handling, or team collaboration. Further assessment in these areas would be beneficial.