Help & Supportcareers@gravityer.com
Python Engineer with 3+ years in Data Analytics & Cloud
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced Python Developer with a strong background in data-driven system development, automation, and cloud integration. Proven ability to optimize data workflows, reduce processing times, and enhance system scalability. Skilled in leveraging Python, SQL, and AWS services to deliver robust solutions for inventory management, reporting, and web data extraction.
Dublin Business School
M. Sc. In Data Analytics · Data Analytics
August 1, 2022 – June 30, 2023
Dr. A. P. J. Abdul Kalam Technical University, Lucknow
B.Tech · Computer Science
August 1, 2013 – June 30, 2017
The Ralph Group
Software Developer
November 1, 2023 – January 1, 2026
Dublin, County Dublin, Ireland
Ulster Bank
Python Developer Intern
July 1, 2022 – August 1, 2023
Dublin, County Dublin, Ireland
DoMySale Pvt. Ltd.
Python Developer
February 1, 2021 – June 1, 2021
Udaipur, Rajasthan, India
The candidate scored 94% on the 'Data Scientist — Artificial Intelligence' exam, indicating a very strong grasp of the core concepts and skills tested.
Strengths
Limitations
Cultural Fit Analysis
The candidate has experience across different company types (The Ralph Group, Ulster Bank, DoMySale Pvt. Ltd.) and roles (Software Developer, Python Developer Intern), suggesting adaptability. The projects involve practical problem-solving and efficiency gains, which aligns with a results-driven culture. The M.Sc. in Data Analytics combined with Python development experience indicates a continuous learning mindset and a blend of analytical and engineering skills, which can be valuable in diverse teams. The focus on automating manual tasks and improving existing systems suggests a proactive and improvement-oriented approach.
Soft Skills & Operational Fit
The candidate's resume highlights a focus on efficiency improvements, problem-solving (e.g., diagnosing slow queries, flagging discrepancies), and automating routine tasks. This indicates a practical, results-oriented approach and a good fit for operational roles requiring process optimization and data integrity. The experience in developing scheduled reports and email summaries also points to reliability and attention to stakeholder needs.