Mayank Gowda | Software Developer

Hi, I'm Mayank Gowda.

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Passionate engineer dedicated to building scalable software and backend solutions to advance humanity in the realm of software engineering.

About

I am a Graduate Student at Carnegie Mellon University pursuing Master of Information Systems Management. Building software solutions for real world applications and architecting backend systems at a global scale fascinates me to a great extent.

Having worked on a plethora of software development tools, languages and frameworks, both in academic and professional environments, I am well equipped to design robust, scalable, pragmatic and efficient products and features.

I thrive in highly uncertain environments by bringing order to chaos. I am highly adaptable to challenging situations and capable of inspiring people around me to achieve a common goal by going above and beyond well as ensuring perfection in my work.

My life's motto is "To make the impossible possible," and I live by this every minute of my life. What was once impossible is possible today because someone out there dared to dream it and do it. And so shall I.

My recent experience with payments and financial services made me fancy the FinTech sector. The need for robust real-time solutions, highly scalable system architecture, extreme accuracy requirements and all other nitty gritties in the finance space is what excites me about it.

Experience

Finix Payments Inc.

Software Engineering Intern

Intern Software Engineer in the Data Engineering wing, a team responsible for building robust data pipelines, scalable infrastructure for data analysis, generating a plethora of reports for clients.
Enhanced report generation pipeline components, AWS Lambdas and SQS Queues, to support intelligent rescheduling of cron jobs of periodic report generation based on payment settlement data populated on AWS Redshift reducing report failures and manual rescheduling by 35%.
Revamped report generation logic to support custom and preset transactions time windows with dynamic adjustment capabilities to support global timezones and holidays.
Collaborated to building data ingestion pipeline for data warehousing of settlement and transaction data from WorldPay and other payment processors.

Tools/Tech: Java, AWS Lambdas, AWS SQS, AWS Redshift,

June 2022 - Aug 2022 | San Francisco, CA

Dish Network

Software Engineer

Engineer in an Agile Development team collectively contributing towards WatchParty, a first of its kind co-viewing feature for watching Live and On-Demand content as a group with Audio and Video conferencing capabilities, across various platforms of SlingTV application.
Jumpstarted career in Web Development by working on Sling web app which was primarily based on JavaScript, React and Redux, where I implemented new sub-features like sync improvements while assisting in maintaining the application in real time.
Worked on improving sync mechanisms in a party based on network and client responsiveness metrics to ensure near zero variation in player playback position across host and the guest users.
Implemented the WatchParty feature on iOS from ground up, on the native Sling TV iOS application, using mostly Swift and some Objective-C and React-Native, which was initiated and completed in a span of 4 months.
Immediately transitioned to Android mobile devices platform, where a similar complete integration with native Sling TV application (based on Java and Kotlin) from square one was achieved, and released in about 3 months, beside assisting and collaborating with a team on Android TV platform.
Overlooked feature extension for Android TV platform by external software development contractors

Tools:

Sep 2020 - Aug 2021 | Bengaluru, KA, India

Dish Network

Software Engineer Intern

Intern engineer in an Agile team developing smart set top boxes for commercial TVs in the Hospitality Industry powered by Android OS.
Designed, developed and unified protocols using C++ and Qt framework for communication and control of commercial TVs of various manufacturers from proprietary set top box, the Dish Evolve.
Integrated protocol with Android OS using Java Native Interface(JNI), Java and Kotlin for controlling TVs over multiple channels like WiFi, Bluetooth and IR Remote Control.
Collaborated with hardware team to design and develop a custom serial communication interface to establish connectivity between the TV and the Dish Evolve box.

Tools:

Jan 2020 - July 2020 | Bengaluru, KA, India

Param Machines & Moulds

Consultant (Operations & IT)

Deployed and configured Windows Server 2019 with Active Directory and Group policy for managing organization digitally and reduce office maintenance staff to 50% by automating repetitive day-to-day operations
Spearheaded digital marketing campaigns to enhance the organization’s digital presence across the country, amplifying annual lead generation by more than 3 times.

July 2020 - Sep 2020 | Bengaluru, KA, India

Pramukh Engineering

Co-Founder / Partner

Remodeled business processes by fostering the use of enterprise tools to effectively track vendors progress and manage workflows to reduce project turnaround time by 30%
Coordinated and delivered project worth over $1M with almost nil capital by leveraging a comprehensive specialized vendor base and outsourcing manufacturing activities.
Managed leads, clients, vendors and projects across India, touring more than 20 cities and manufacturing plants, doubling the clients and vendors in numbers.

Dec 2016 - Dec 2019 | Bengaluru, KA, India

Projects

WeChat Application

A multi-cloud, scalable RESTful microservices architecture for a monolithic Chat application using Docker and Kubernetes.

Accomplishments

Transformed a monolith application into RESTful real-time and scalable web services based on microservice architecture using Docker and Kubernetes
Develop Dockerfiles, build Docker images and deploy Docker containers by constructing and deploying Helm charts to containerize RESTful Spring applications.
Configured and managed Kubernetes clusters for deploying application containers on multiple clouds(Google and Azure)
Create container registries and push custom Docker images to the registries
Identified service failures, routed traffic away from a failed cluster and scale up services in the healthy cluster using autoscaling rules.
Define, manage and monitor global routing based on performance and availability using Azure Front Door Service
Tools: Docker, Kubernetes (GKE and AKS), MySQL, Nginx, Helm, Terraform
Cloud Platform: Google Cloud, Microsoft Azure

Heterogenous Database for Yelp

Design schemas with data population and efficient queries for SQL and NoSQL databases for Yelp.

Accomplishments

Design and develop efficient database queries using the Java API for databases to fetch data from heterogeneous SQL and NoSQL databases.
Design relational database on MySQL, along with efficeint querying by implementing MySQL indexing for improved performance.
Design distributed database for Yelp on HBase along with table schema and row key for even data distribution across different region
Tools: MySQL, Apache HBase, ORM(Object Relational Mapping), JDBC, Terraform
Cloud Platform: Microsoft Azure

Ride booking app with Ad Matching

Developed an Uber-like ride booking app backend, with real-time data streams by adopting stream processing using Kafka and Samza.

Accomplishments

Developed and deployed a solution on Yarn cluster to handle real-time data streams using a Kafka to produce streams and consume Samza for processing on AWS EMR.
Implemented driver match feature based on real-time driver gps location events, driver preferences, user location, based on a weighted calculation logic.
Designed an Ad-Match feature with appropriate revenue distribution for personalized ads based on user intersts, location, nearby businesses and user financial data.
Tools: Apache Kafka, Apache Samza, Apache Yarn, AWS Elastic MapReduce
Cloud Platform: Amazon Web Services

ML model for Fare Prediction

Designed, developed, trained and deployed ML model for fare prediction with text, speech and image support along with feature engineering.

Accomplishments

Inspected and visualized provided data to identify, construct and evaluate new and disrciminating features using feature engineering methods to maximize accuracy of an ML-based predictor.
Trained a ML model (XGBoost) predictor utilizing the constructed features and training data and tuned hyperparameters to improve predictor accuracy on Google AI Platform
Deployed and evaluated an end-to-end solution requiring pipeline of cloud ML APIs and custom trained ML models on Google App Engine (GAE).
Extended API to supprt Speech-to-Text and Text-to-Speech using Natural Language along with images using Cloud Vision and AutoML.
Tools: Python, Flask, Pandas, Google AI Platform, Google App Engine,AI Platform Training & Prediction API, Cloud Text-to-Speech API, Cloud Speech-to-Text API, Cloud Natural Language API, Directions API, Cloud Vision, AutoML
Cloud Platform: Google Cloud

Scalable Backend on AWS

Architected a horizontally scalable compute backend on AWS for handling extreme dynamic loads using SDK, CLI and Terraform.

Accomplishments

Designed and implemented a highly scalable compute backend infrastructure for highly dynamic loads using AWS SDK on Java, CLI and Terraform.
Developed solutions to monitor cloud resource metrics on CloudWatch and manage cloud resources to handle resource failure using Elastic Load Balancer.
Analyzed load patterns and account for cost as a constraint to develop elastic policies for Auto Scaling Group to maintain the requried Quality of Service (QoS) with appropriate performance tradeoffs due to budget constraints.
Tools: Azure Managed SQL, MongoDB, Neo4j Graph Database, Terraform
Cloud Platform: Amazon Web Services

Social Network Web Service

Designed multiple databases on MySQL, MongDB and Neo4j for a social network web service.

Accomplishments

Designed, configured, populated and deployed different SQL, NoSQL, GraphQL heterogeneous storage databases for different data models.
Designed effective database schemas based on application requirements and efficient querying to fetch data from the heterogenous databases storge.
Provisioned, configured and managed cloud resources to provide several NoSQL databases and a Database-as-a-Service (DBaaS) cloud offering.
Implemented database indexing on MySQL and NoSQL databases with caching mechanisms to improve query performance./li>
Tools: Managed MySQL, MongoDB, Neo4j GraphQL, Terraform
Cloud Platform: Microsoft Azure