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Shantanu Borde

@shantanuborde1

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Database specialist with 3+ years of experience in data engineering.

India

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What I'm looking for

I am looking for a role that allows me to leverage my database skills in a collaborative environment, focusing on data engineering and analytics while providing opportunities for growth and learning.

I am a dedicated Database Specialist with over three years of experience in building systems to process and analyze high-volume financial transactions. My expertise lies in SQL optimization, data handling, and performance tuning, which has allowed me to contribute significantly to production issues and archival strategies. Recently, I have expanded my skill set to include writing simple ETL pipelines and Python-based audit tools, showcasing my adaptability and eagerness to grow in the field of data engineering.

During my tenure at Oracle Financial Software Services, I successfully redesigned a sensitive archival job that drastically reduced runtime by 88%, enabling the handling of 600k rows in just 28 minutes. My contributions have been recognized, as I ranked 2nd among 14 Subject Matter Experts for my critical backend contributions and received the Oracle Pacesetter Award for my consistent support and delivery. I am passionate about leveraging my skills to enhance system visibility and efficiency while mentoring junior team members.

Experience

Work history, roles, and key accomplishments

Current

Associate Consultant

Current

Oracle Financial Software Services

Jul 2022 - Present (3 years 2 months)

Redesigned a sensitive archival job, reducing runtime by 88% and handling 600k rows in 28 minutes while preserving ACID compliance. Built an automated export of archived data using Oracle Data Pump and transferred it to S3 via Bitbucket, reducing primary DB storage costs by 60%.

SQL Oracle Data Pump S3 Bitbucket ETL Performance Tuning Indexing Caching Load Balancing

Project Intern

Prescient Technologies

Nov 2021 - Jun 2022 (7 months)

Built a 3D Generative Adversarial Network (GAN) model for engineering parts, replacing an older VAE-based model. This improved model output quality and increased accuracy from 51.8% to 73.6%, while reducing average model training time by 25%.

Generative Adversarial Networks (GANs)Machine Learning Model Training Python

Education

Degrees, certifications, and relevant coursework

Pune Institute of Computer Technology

Bachelor of Engineering, Electronics & Telecommunication

2018 - 2022

Grade: 8.42 CGPA

Activities and societies: Participated in IEEE Credenz Tech Fest and department-level technical events

Graduated with an 8.42 CGPA, focusing on Machine Learning and Artificial Intelligence. Participated in IEEE Credenz Tech Fest and department-level technical events.