Selected Works
Below is a curated selection of my work across Graph Infrastructure, Big Data, and Product Design. My focus is always on bridging the gap between complex backend logic and intuitive, business-driven solutions.
Below is a curated selection of my work across Graph Infrastructure, Big Data, and Product Design. My focus is always on bridging the gap between complex backend logic and intuitive, business-driven solutions.
Software Engineering Manager, Linkedin
What was the Challenge?
As LinkedIn grew, the legacy infrastructure for different services e.g., "People You May Know" and other graph-dependent features became a bottleneck. We needed a system that could handle billions of edges with sub-second latency while simplifying the onboarding of new data clients.
What we did?
I led the engineering strategy for the LIquid Client Framework, architecting a standardized ingestion pipeline and leading a cross-functional team through the high-stakes migration of mission-critical services.
What was the impact?
Successfully modernized the infrastructure, significantly reducing the "drama" of large-scale data migrations and accelerating the time-to-market for new graph-powered features.
SoftwareEngineering Manager | Technical Lead, Oracle
What was the challenge?
Making graph technology accessible within the Oracle ecosystem required a robust, scalable middleware that could translate complex graph queries into efficient database operations.
What we did?
I led the development of the Property Graph Middle Tier, focusing on creating a "low-friction" developer experience. I collaborated closely with product teams to ensure the API was both powerful and predictable.
What was the Impact?
This work became a cornerstone of Oracle’s graph offering, enabling enterprise clients to run social network analysis and fraud detection at a massive scale.
Principal Engineering Manager , Microsoft
What was the Challenge?
Modern enterprise data is often fragmented across massive data lakes, making it nearly impossible to analyze complex relationships at scale. We needed to build a "zero-to-one," scale-out Labeled Property Graph (LPG) analytics engine that could live natively within Microsoft Fabric, requiring both deep technical innovation and seamless global execution.
What we did?
I led the "zero-to-one" development of the analytics engine, mentoring a distributed team across the Bay Area and Seattle while partnering with the lead architect to define the product's "North Star" roadmap. To ensure global velocity, I established engineering best practices that enabled us to seamlessly onboard and integrate a new engineering hub in Barcelona.
Beyond the code, I transformed organizational communication. I conceived and launched an executive newsletter and a centralized SharePoint hub to provide leadership with clear visibility into our progress. I also founded a bi-weekly "Brown Bag" series, facilitating 10+ sessions to synthesize knowledge sharing across the entire Fabric Graph organization.
What was the Impact?
Successfully bridged the gap between engineering and the customer by building industry-specific POCs that defined our core storage and compute requirements. This work didn't just build a tool; it established the cultural and technical foundation for the next generation of graph analytics at Microsoft.
Leading the Intersection of Engineering & UI/UX at Oracle
What was the challenge?
Graph databases are notoriously difficult to visualize. The goal was to build a tool within the Oracle Autonomous Database (ADB) that allowed users to model their data visually without needing to be graph experts.
What we did?
I stepped into a hybrid role, pairing directly with a Senior PM to design the wireframes and UX flow. I then led the engineering team to build the design-to-implementation pipeline, ensuring the backend logic supported a seamless drag-and-drop experience.
What was the Impact?
Delivered an industry-leading visual modeling tool that lowered the barrier to entry for graph technology, empowering non-technical users to derive insights from complex data sets.
Technical Lead, Oracle
What was the Challenge?
Major financial institutions needed to prove that graph technology could detect sophisticated fraud rings faster than traditional relational databases.
What we did?
I engineered and presented high-impact POCs for top-tier US and International banks. This involved mapping complex financial transactions into graph schemas to identify "circular" patterns and suspicious entities.
What was the Impact?
These POCs directly resulted in secured partnerships, proving that our graph infrastructure could solve multi-billion dollar fraud challenges in real-time.