Avenash is available for hire
Hire AvenashAvenash Kabeera
Verified Expert in Engineering
Software Developer
Singapore, Singapore
Toptal member since December 10, 2019
Bio
Avenash has 15+ years of experience in all areas of the software development lifecycle, with a proven track record in developing web applications, back-end services, and external APIs. He is an engineering leader and mentor with experience in building and scaling high-performance teams in companies at various stages, guiding software architecture, design, and implementation, and managing stakeholders across executives, product, strategy, operations, and business development functions.
Portfolio
Affinidi
Agile, Agile Software Development, React, TypeScript, Node.js...
Agoda
Spark, Python, Scala, Apache Hive, Hadoop, Object-oriented Programming (OOP)...
Clients
wxWidgets, Perl, C++
Experience
- C++ - 12 years
- Windows - 10 years
- Object-oriented Programming (OOP) - 10 years
- Git - 5 years
- Python - 4 years
- Agile Software Development - 4 years
- Perl - 4 years
- TypeScript - 2 years
Availability
Part-time
Preferred Environment
Git, Visual Studio Code (VS Code), Windows
The most amazing...
...project I've worked on is building an enterprise-level portfolio-reporting batch web app that allows clients to administer report generation by the 100,000s.
Work Experience
Software Engineering Manager
2022 - 2023
Affinidi
- Collaborated with product, strategy, and business development to define product vision and roadmaps for a decentralized trusted data exchange leveraging decentralized identity by verifiable credentials.
- Provided technical guidance and expertise in client interactions throughout the entire sales cycle.
- Designed the microservices architecture for the Ceal ecosystem for quick product validation, enabling fast pivots to new use cases.
- Developed the Ceal enterprise portal from ideation to production, providing Credential Issuance capabilities, and seamless OAuth integration with users' credentials wallet.
- Initiated the development of a new QA framework for the Ceal mobile app to automate QA testing, saving product owners 50+ hours of manual testing for every release.
- Implemented engineering best practices, including comprehensive design and coding guidelines and a rigorous code review process, enabling teams to build more robust, maintainable, and testable applications.
- Set up and maintained CI/CD pipelines for 13 microservices via Terraform (infrastructure as code), enabling easier deployments to AWS.
- Built three engendering teams of 19 engineers, as a software engineering manager.
- Built a culture of "freedom and responsibility" to instill a strong learning and growth mindset and high autonomy with accountability, resulting in the highest promotion rate and fastest progression across the entire organization.
Technologies: Agile, Agile Software Development, React, TypeScript, Node.js, Distributed Software, Microservices, System Design, NestJS, Next.js, Jest, DocumentDB, Redis
Senior Machine Learning Engineer | Technical Lead
2020 - 2022
Agoda
- Rearchitected Spark jobs and pipelines to execute tasks independently, increasing stability by over 50% without disrupting existing production processes.
- Redesigned and implemented Room Mapping Streamline Spark job into producer/consumer pattern to enable parallel execution of multiple instances, increasing 25%+ in throughput.
- Collaborated with product owners to A/B test product hypotheses, improving user experience and business metrics, including a 5% increase in daily room booking.
- Developed robust data pipelines incorporating machine learning models and matching algorithms to process massive supplier data (100+ TB/run), often incorrect and fragmented, to achieve 99.9% accuracy in room mapping.
- Optimized core ETL job to process around 300 million records daily, reducing memory usage by 85%.
- Developed a web application and SOP to enable self-service configuration for the Room Mapping Rules Engine for the operations team, saving 10+ dev hours per week.
- Worked closely with data scientists to train and integrate new machine learning models into current property mapping and streamline targeting properties in the Chinese language.
Technologies: Spark, Python, Scala, Apache Hive, Hadoop, Object-oriented Programming (OOP), Data Structures, Agile Software Development
Software Engineer
2020 - 2020
Clients
- Designed and developed a new C++ UI and framework to replace the client's legacy process to optimize the DeltaV workflows for automation, optimizing operational efficiency and providing a better user experience.
- Deployed software as a Windows application with Microsoft Installer to encapsulate all existing process dependencies, removing manual setup and configuration for end-users.
- Packaged the application into a Microsoft Installer that sets up all its dependencies, allowing end-users to immediately get going.
- Assessed various licensing models and implementation roadmaps leveraging different solution stacks to develop final recommendations for the client.
Technologies: wxWidgets, Perl, C++
Lead Software Engineer
2016 - 2019
FactSet
- Led three engineering teams across global offices to develop and maintain 10 applications in the portfolio analytics division.
- Initiated the project to create a unified web application, Portfolio Reporting Batcher, to replace four legacy batching applications, delivering a one-stop solution for clients' batching workflows.
- Designed a long-running infrastructure to offload Portfolio Reporting Batcher's complex operations to background processes, significantly increasing the success rate of job runs by 40%.
- Created a centralized Batch API to orchestrate and manage 50,000+ reports per job, reducing code redundancy by over 30%.
- Led the design and development of an automated conversion system to seamlessly migrate 10,000+ client documents and jobs onto the next-gen platform, saving product managers six months of manual work.
- Collaborated with project managers and other engineering groups to plan and prioritize projects for engineering teams.
Technologies: Redis, AngularJS, Node.js, JavaScript, TypeScript, C++, Agile, Scrum, Engineering Management, Technical Leadership, MySQL, Perl, Object-oriented Programming (OOP), Agile Software Development
Senior Software Engineer
2007 - 2016
FactSet
- Built Private Wealth Manager application from scratch, introducing FactSet into the wealth management space, now becoming the foundation of the FactSet next-generation Wealth solutions.
- Built a prototype web application over one weekend and convinced senior management to invest in migrating the legacy Portfolio Publisher to a new web app.
- Redesigned legacy Portfolio Batcher infrastructure from running jobs in-process to running with distributed services, improving scalability and stability with no disruption to clients’ production processes.
- Created a unified API to replace the different legacy frameworks used by three Portfolio Publisher applications, reducing the number of client issues by more than 50%.
Technologies: JavaScript, TypeScript, AngularJS, C++, Technical Leadership, Engineering Management, Object-oriented Programming (OOP), REST APIs, Data Structures, Agile Software Development
Experience
A File Downloader Module for a Web Crawler
https://github.com/akabeera/file-downloaderA Python module that can be used on its own or integrated into a web crawler for downloading media from the internet. The file downloader supports various protocols such as HTTPS, FTP, and SFTP and even has an interface where consumers can plug in their custom modules.
The file downloader is very robust in that it's able to support huge files (50GB+ range) without timing out, it's ready to automatically restart a download in the event of losing internet connection, and it allows you to control the memory usage of each download.
It is also very configurable. You can specify the number of files to download in parallel, by size, and to break each file while downloading. You can also specify the max timeout for connecting to a server as well as waiting for server activity during a file download.
The file downloader is very robust in that it's able to support huge files (50GB+ range) without timing out, it's ready to automatically restart a download in the event of losing internet connection, and it allows you to control the memory usage of each download.
It is also very configurable. You can specify the number of files to download in parallel, by size, and to break each file while downloading. You can also specify the max timeout for connecting to a server as well as waiting for server activity during a file download.
Workflows Automation MVP
• Designed and developed a C++ UI and framework to replace the client's legacy process to optimize the DeltaV workflows for automation, improving operational efficiency and user experience (C++, wxWidgets, Windows Development).
- Deployed software as a Windows application with Microsoft Installer to encapsulate all existing process dependencies, removing manual setup and configuration for end-users (C++).
• Assessed various licensing models and implementation roadmaps leveraging different solution stacks to develop final recommendations for the client.
- Deployed software as a Windows application with Microsoft Installer to encapsulate all existing process dependencies, removing manual setup and configuration for end-users (C++).
• Assessed various licensing models and implementation roadmaps leveraging different solution stacks to develop final recommendations for the client.
Education
2011 - 2013
Master of Science Degree in Quantitative Methods and Modeling
Baruch College - New York City, NY, USA
2003 - 2007
Bachelor of Science Degree in Computer and Electrical Engineering
NYU Tandon School of Engineering - New York City, NY, USA
Certifications
MARCH 2020 - PRESENT
Sequence Models
Coursera
SEPTEMBER 2019 - PRESENT
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization
Deeplearning.ai via Coursera
SEPTEMBER 2019 - PRESENT
Structuring Machine Learning Projects
Deeplearning.ai via Coursera
AUGUST 2019 - PRESENT
Neural Networks and Deep Learning
Deeplearning.ai via Coursera
JANUARY 2019 - PRESENT
Machine Learning
Stanford University via Coursera
Skills
Libraries/APIs
wxWidgets, React, Node.js, NumPy, REST APIs
Tools
Git, Draw.io
Languages
C++, Python, JavaScript, JavaScript 5, Perl, TypeScript, SQL, Java, Scala, Python 3, XSLT
Paradigms
Agile Software Development, Object-oriented Programming (OOP), RESTful Development, Unit Testing, Agile, Scrum, Microservices
Platforms
Windows, Visual Studio Code (VS Code), Visual Studio 2017, Jupyter Notebook
Frameworks
AngularJS, Express.js, Flask, Spark, Hadoop, NestJS, Next.js, Jest
Storage
MySQL, PostgreSQL, Redis, Apache Hive, Data Pipelines
Other
Data Warehouse Design, Quantitative Analysis, Statistics, Data Structures, Algorithms, Operating Systems, Linear Algebra, Differential Equations, Image Processing, Signal Processing, Software Engineering, Regression, Quantitative Modeling, Engineering Management, Technical Leadership, Machine Learning, Big Data, Neural Networks, Deep Learning, Distributed Software, System Design, DocumentDB
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