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Data Engineer with 5+ years in Banking & Credit Risk Analytics
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Result-driven Data Analyst with 4+ years of experience in Banking and Credit Risk Analytics. Expertise in data cleaning, transformation, and advanced SQL-based analysis to drive business insights and risk optimization. Skilled in building automated reporting pipelines, ETL workflows, and interactive dashboards using SQL, SAS, Alteryx, Python, GCP (BigQuery), and Tableau. Proven ability to handle large-scale financial datasets and deliver data-driven solutions for credit decisioning and portfolio monitoring.
RGPV University
Bachelor of Engineering
August 1, 2012 – June 30, 2016
Muthoot Finance
Data Engineer
May 1, 2025 – Present
India
DBS Bank
Data Analyst
February 1, 2024 – April 1, 2025
India
Bhagirath Motors Private Limited
Technical Manager
September 1, 2023 – January 1, 2024
India
HDFC Bank
Associate Data Analyst
November 1, 2020 – August 1, 2023
India
Alteryx Designer Core Certification
Unknown
June 1, 2026 – Present
HackerRank SQL (Intermediate)
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in the financial services industry, specifically banking, which aligns well with roles requiring domain-specific knowledge in credit risk and financial data. Their progression from Data Analyst to Data Engineer roles, coupled with experience in diverse projects (e.g., loan portfolios, customer segmentation, risk assessment), indicates adaptability and a broad skill set. The brief stint as a Technical Manager outside of data engineering is an outlier but doesn't significantly detract from their core data profile. The certifications in Alteryx and HackerRank SQL further demonstrate a commitment to skill development.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills, particularly in complex financial data environments. Their experience in leading projects and collaborating with cross-functional teams indicates good operational fit. The detailed descriptions of their work suggest a results-driven and proactive approach. However, without direct assessment, communication and teamwork soft skills are inferred from project descriptions.