Used programming language
JavaScript, Golang, Java, Clojure, Ruby, Python
portfolio.
Showcase of my craft.
Portfolio
Crafting strong systems requires skill — and skill comes from hard-won experience
Systems, platforms, and product tooling built across data, infrastructure, and growth.
A showcase of my engineering projects and technical achievements
Breadth map
A scan of domains, stacks, and systems
Built across data, platform, and product tooling. This is the fastest way to understand the range.
Built systems on top of
Apache Flink, Apache Kafka, Websocket, Rest, BigQuery, PostgreSQL, React, Kubernetes, Terraform, GCP, MaxCompute
Systems I've crafted
Web UI, Data Ingestion, Analytics, ETL, Deployment solution, Streaming Engine
Metrics
Impact in numbers
A few quantitative anchors that show scale and outcome.
7+
Years in Engineering
3 Mio +
Of Dollars Saved From Successful Projects
50+
People Mentored
Impact highlights
Narrative snapshots across systems
Each system tells a different outcome story. These are the quick reads before the deep dives.
Data Streaming Platform
In an organization that heavily adopts Apache Kafka and event-driven architecture, Kafka events become a critical asset — enabling the development of various applications that react to real-time data.
Real-Time Fraud Detection Migration Support
Migrated fraud detection rules from batch to stream processing, enabling immediate fraud detection through Apache Flink. Improved system responsiveness and detection accuracy.
One-Click Deployment Solution
Developed a one-click deployment tool to simplify and streamline application release workflows, reducing manual steps and improving developer productivity.
Clickstream Ingestion
Clickstream data is essential for marketing analytics and product development. However, collecting and managing this data presents several challenges. The ingestion system must be scalable to handle the high volume of user-generated events. It must also support flexible schemas to accommodate variations across event types. Additionally, the high frequency of incoming data requires careful selection of the communication protocol to ensure efficiency.
Raccoon implementation
Developed a Go-based ingestion service to collect clickstream data via WebSocket and forward it to Kafka. Built according to a technical RFC and designed to scale for petabytes of daily traffic per data partition. Later extended to support additional protocols.
Open-Source Raccoon
Open-sourced the Mercury ingestion service as [Raccoon](https://github.com/goto/raccoon), enabling broader community use for scalable event ingestion. Contributed to documentation, production hardening, and feature generalization to support various protocols.
Customer Segmentation Engine
Being able to define customer segments based on user behavior and attributes is essential for effective marketing. Traditionally, creating these segments requires marketers to identify data sources, write SQL queries, and manually execute them — a process that is tedious, error-prone, and time-consuming.
Rule-Based User Segmentation Engine
Designed and developed a scalable user segmentation engine to power marketing use cases. Replaced a 3rd-party tool, resulting in millions of dollars in annual savings.
Clickstream Analytics Redesign
An internal platform was developed to support analytics on top of clickstream data, primarily for product analytics. It allowed users to visualize trends, build dashboards, browse a catalog of clickstream events, and trace individual user activity.
Analytics Platform Redesign
Redesigned key features of an internal analytics platform by identifying and resolving performance bottlenecks. Improved performance and significantly reduced operational costs.
A/B Testing Platform
A/B testing allows product teams to optimize experiences based on data rather than assumptions. To enable this, an internal A/B testing platform was developed.
UI Revamp Implementation
Revamped the UI of an internal A/B testing platform, significantly improving usability and user experience for experiment owners and analysts.
In-House Experimentat Analytics Platform
Collaborated with the experimentation team to reverse-engineer Eppo and design an in-house experimentation analytics platform. Led system design and oversaw implementation, replacing a third-party solution with a custom architecture tailored to internal needs.
organizations where I honed my craft as engineer and mentor