Data Engineer with 2+ years in ETL/ELT pipelines & Data Analysis
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Data Engineer and Analyst with 2.7 years of experience at Capgemini and Amazon, working across the full data lifecycle - from building and maintaining ETL and ELT pipelines on Snowflake to writing advanced SQL, performing exploratory data analysis, and delivering structured reports and dashboards to business stakeholders. Experienced in handling large-scale datasets, ensuring data quality, and translating complex data into clear, actionable insights for non-technical teams.
Visvesvaraya Technological University (VTU)
Bachelor of Engineering (B.E.) · Information Science
August 1, 2019 – June 30, 2023
Capgemini
Data Engineer
November 1, 2024 – Present
Bengaluru, Karnataka, India
Amazon Development Centre India
Data Quality Analyst - Catalog Operations
September 1, 2023 – November 1, 2024
Bengaluru, Karnataka, India
GenAI-Enabled Data Reporting Automation (POC)
June 1, 2026 – Present
Built an end-to-end POC integrating Python and Amazon Bedrock to auto-generate plain-language insight summaries from SQL query outputs - reducing manual reporting effort by ~40% in testing and turning raw data tables into readable analytical reports. Applied EDA, data storytelling, and statistical analysis techniques to validate output quality and make insight delivery scalable without manual analyst effort.
Azure AI Fundamentals
Microsoft
June 1, 2026 – Present
Snowflake Training
Degreed & Pluralsight
June 1, 2026 – Present
Python for Data Science
Udemy
June 1, 2026 – Present
SQL & Python Scripting
Ocean Certification
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience across Capgemini and Amazon, coupled with a project involving GenAI, indicates adaptability and a proactive approach to learning new technologies. Their focus on improving reporting efficiency and data quality aligns well with a results-oriented culture. The breadth of skills and certifications suggests a commitment to continuous professional development.
Soft Skills & Operational Fit
The candidate demonstrates strong cross-functional collaboration, stakeholder communication, and attention to detail, which are critical for operational success in a data engineering role. Their experience in data quality analysis at Amazon also highlights a methodical approach to problem-solving and process improvement.