Aviral Petwal

Software Engineer

Redmond, Washington, United States5 yrs 5 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in building scalable data pipelines.
Proficient in AWS services for data engineering.
Strong foundation in machine learning and AI.

Stackforce AI infers this person is a Data Engineering and Software Development professional with a focus on SaaS solutions.

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Skills

Core Skills

SqlData WarehousingSoftware DevelopmentApi DevelopmentData EngineeringEtlData Analysis

Other Skills

SQL TuningMySQLCommunicationPythonRepresentational State Transfer (REST)JavaScriptGraphQLGitRESTAmazon RedshiftSAS (Software)Data MartsExtract, Transform, Load (ETL)Machine LearningArtificial Intelligence

About

As a data engineer at Lead, I developed and maintained scalable and robust data pipelines to support the company's educational platform and products. I worked extensively on AWS ecosystem, using services such as Redshift, S3, Lambda, Kinesis, and Glue to handle real-time and batch data ingestion, processing, and analysis. I also implemented data quality checks, monitoring, and alerting systems to ensure data reliability and accuracy. I am currently pursuing a master's degree in Computer Science at the State University of New York at Buffalo, where I am learning advanced topics in data science, machine learning, and artificial intelligence. I am proficient in Java, Python, and C++, and have completed several courses and certifications related to neural networks, deep learning, and machine learning projects. I am passionate about applying my skills and knowledge to solve real-world problems and create innovative solutions.

Experience

5 yrs 5 mos

Total Experience

1 yr 9 mos

Average Tenure

2 yrs

Current Experience

Microsoft

Software Developer

Jun 2024 – Present · 2 yrs · Redmond, Washington, United States · On-site

Odoo

Full Stack Engineer Intern

Jun 2023 – Aug 2023 · 2 mos · Buffalo, New York, United States · On-site

Developed a custom Postman service for Odoo Environment. The Odoo API Connector is a module designed to facilitate interactions with external APIs in Odoo.
It supports REST and GraphQL API requests, real-time data streaming via WebSocket, response handling, and action triggering based on API responses.
Users can configure API connections, handle responses, and perform OAuth2 authentication. It also offers Postman collection support and allows customization through Python code.

SQLPythonCommunicationRepresentational State Transfer (REST)JavaScriptGraphQL+3

University at buffalo

Graduate Grading Assistant

Feb 2023 – Dec 2023 · 10 mos · Buffalo, New York, United States · On-site

Working as a graduate grader in the course Data Modeling and Query Language (CSE 560)

SQL TuningMySQLCommunicationData WarehousingSQL

Lead school

Data Engineer

Oct 2020 – Jul 2022 · 1 yr 9 mos · Bengaluru, Karnataka, India

Amazon RedshiftSQL TuningMySQLCommunicationSAS (Software)Data Warehousing+6

Amadeus

2 roles

Software Developer

Jul 2019 – Oct 2020 · 1 yr 3 mos

Amazon RedshiftSQL TuningMySQLCommunicationSAS (Software)Software Development+2

Software Developer Internship

Jan 2019 – Jun 2019 · 5 mos

Working in a log analytics team to recognize patterns for anomaly detection using different machine learning algorithms.
Used Splunk to set up a log analytics platform for efficient error monitoring. Sending data to Splunk using Kafka Producer and JMS queue.
Currently working on predictive analysis of system logs using machine learning algorithms and toolkits provided by Splunk.

MySQLCommunicationSAS (Software)Software DevelopmentGitData Analysis

Chennai mathematical institute

Student Intern

May 2018 – Jul 2018 · 2 mos · Chennai, Tamil Nadu, India

Designed a Music Classifier using Deep Neural Network. Designed Music Generator using Recurrent Neural Network (RNN) based on LSTM architecture. Implementation of Reinforcement Learning (RL) and GAN to improve the performance/accuracy of RNN generated music.
The aim of the project was to determine the total number of corn plants in a given field. The aerial photograph and video of the field were captured using a drone. Image processing techniques used to suppress the noise from the virgin image. A Deep Neural Network developed and trained to process the filtered image and count the number of plants. The accuracy of counting is better than 90%.

Raja ramanna centre for advanced technology (rrcat)

Student Intern

Dec 2017 – Jan 2018 · 1 mo · Indore, Madhya Pradesh, India

The electron accelerator produce high energy electron beam, which possesses Gaussian distribution of the particles
Developed a MATLAB code for analysis of the beam image captured on radiochromic film.
The code is used to determine electron beam characteristics such as beam profile, beam size and position