PRATIK BABAR

AWS Cloud Engineer

https://talent.gravityer.com/pratik-babar

AWS Cloud Engineer with 2+ years in Cloud Infrastructure & Data Engineering

Codify Software Services

Key Strengths

Proficient in core AWS services (EC2, S3, VPC, RDS, Redshift, IAM, CloudWatch, Auto Scaling, CloudFormation, AWS Glue, AWS Lambda).
Demonstrated experience in designing and deploying scalable, highly available cloud architectures on AWS.
Strong background in ETL pipeline development and data processing using AWS Glue, S3, and Redshift.
Experience with Python and SQL for scripting and data manipulation.
Understanding of DevOps practices including CI/CD, Docker, and Infrastructure as Code (CloudFormation).

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

AWS Cloud Engineer with 2+ years of experience in designing scalable cloud infrastructure and building data pipelines using AWS services. Skilled in EC2, S3, VPC, RDS, Redshift, and ETL workflows using Python and SQL. Experienced in cloud automation, monitoring, and big data processing with Apache Spark and Airflow. Strong understanding of DevOps practices and data-driven solutions.

Top Skills

PythonSQLVersion Control

Skills

PythonSQLData StructuresObject-Oriented Programming (OOP)Query OptimizationStored Procedureswindow-functionsETL PipelinesData WarehousingData ModelingApache SparkApache AirflowAmazon RedshiftBatch ProcessingData ProcessingS3IamCloudWatchCloudformationAws GlueAWS LambdaGitCiCdDockerVersion ControlAlertingPower BIExcelPandasNumpyMatplotlibSeaborn

Education

Progressive Education Society's Modern College of Engineering

Bachelor of Engineering · Artificial Intelligence and Machine Learning

July 1, 2021 – April 1, 2025

Manere High School and Junior College

Higher Secondary School Certificate

May 1, 2019 – June 1, 2021

Projects

Cloud-Native High Availability Web Architecture on AWS

June 29, 2026 – Present

Designed and deployed a scalable and highly available architecture on AWS using EC2, Application Load Balancer, and Auto Scaling, ensuring 99.9% application uptime. Built a secure VPC with public and private subnets, improving network isolation and strengthening access control. Configured Auto Scaling policies to handle dynamic traffic, supporting up to 30% increase in user load without performance degradation. Deployed Amazon RDS in a private subnet with Multi-AZ configuration, improving database availability and reliability. Implemented CloudWatch monitoring and alerting, reducing system downtime by 20% through proactive issue detection.

Airline Data Ingestion and Analytics Pipeline on AWS

June 29, 2026 – Present

Developed a scalable ETL pipeline to process 10GB of airline and airport data per day using AWS S3, Glue, and Redshift. Optimized data transformation workflows in AWS Glue, reducing processing time by 20% and improving overall pipeline efficiency. Built automated data ingestion and transformation scripts using Python and SQL for consistent and reliable data processing. Stored raw data in Amazon S3 and loaded processed data into Amazon Redshift, improving query performance for analytics. Designed a structured and reliable data pipeline, improving data availability and supporting business reporting and insights.

Key Strengths

Proficient in core AWS services (EC2, S3, VPC, RDS, Redshift, IAM, CloudWatch, Auto Scaling, CloudFormation, AWS Glue, AWS Lambda).
Demonstrated experience in designing and deploying scalable, highly available cloud architectures on AWS.
Strong background in ETL pipeline development and data processing using AWS Glue, S3, and Redshift.
Experience with Python and SQL for scripting and data manipulation.
Understanding of DevOps practices including CI/CD, Docker, and Infrastructure as Code (CloudFormation).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects demonstrate a strong alignment with the target role of an AWS Cloud Engineer, showcasing practical experience in cloud architecture, data engineering, and DevOps. The breadth of AWS services and related technologies (Python, SQL, Docker, Spark) indicates a versatile skill set. The current role as an AWS Cloud Engineer further strengthens the cultural fit. However, the limited professional experience (starting January 2024) suggests a need for further validation of sustained performance and adaptability in diverse team environments.

Soft Skills & Operational Fit

The candidate's project descriptions indicate an ability to design and implement robust solutions, suggesting good problem-solving and execution skills. The focus on optimizing processes and ensuring high availability points to a detail-oriented and reliable work attitude. However, without specific psychometric or English test results, a comprehensive assessment of soft skills like logical reasoning, stress handling, and team collaboration is not possible.