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Skills
Tools and technologies I use to deliver reliable, observable, and secure software.
Backend
DevOps
Data
Frontend
AI-Enhanced Development
Kubernetes — Scaling & Optimization
Practical experience designing autoscaling and resource strategies to improve reliability and reduce cost. Focus areas include Horizontal Pod Autoscaler (HPA) for scaling pods by CPU/memory or custom metrics, Vertical Pod Autoscaler (VPA) for right-sizing pod resource requests, and using the Cluster Autoscaler for node-level scaling.
- Horizontal vs. Vertical scaling: HPA (scale replicas) and VPA (adjust resource requests/limits).
- Autoscaling pods on CPU/memory and custom metrics (Prometheus adapter / external metrics).
- Resource requests & limits tuning to reduce throttling and optimize cluster utilization.
- Cluster Autoscaler and node sizing to balance cost and performance.
- Observability + readiness/liveness probes to ensure safe scaling and rollout behavior.
Kafka — High-Throughput Messaging & Reliability
Extensive experience architecting and tuning Apache Kafka for mission-critical systems requiring high throughput, message durability, and real-time processing. Skilled in optimizing producer–consumer performance, managing backpressure, and ensuring data integrity across distributed clusters.
- Designed and optimized Kafka topologies supporting 5k+ TPS across multi-microservice environments.
- Implemented partitioning strategies, consumer group balancing, and concurrency controls to maximize parallelism and minimize lag.
- Enabled dynamic scaling of Kafka consumer applications based on consumer lag and CPU utilization, using sticky assignors to prevent stop-the-world rebalances.
- Developed Kafka Connect integrations for ETL ingestion and data synchronization between databases and external APIs.
- Created retry, backoff, and dead-letter workflows ensuring guaranteed delivery and fault isolation.
- Applied fine-grained producer and consumer tuning (batch.size, linger.ms, fetch.min.bytes) to improve throughput and latency.
- Instrumented topic health monitoring and lag tracking with Dynatrace and custom metrics dashboards.
Spring Batch — Large-Scale Data Processing
Proficient in designing scalable Spring Batch jobs for high-volume ETL and enrichment pipelines, enabling efficient, fault-tolerant data ingestion at enterprise scale.
- Built parallelized file ingestion and transformation pipelines handling 4M+ records per run with chunk-oriented processing.
- Implemented partitioned step execution and asynchronous task scheduling for optimal performance.
- Integrated Spring Batch with Kafka Connectors for streaming and downstream data propagation.
- Created custom retry, skip, and checkpoint logic to ensure transactional consistency and graceful recovery.
- Optimized memory and commit intervals to balance throughput and stability during large-scale batch runs.
Projects
Selected work showcasing delivery of stable, data-informed platforms.
Bulk Messaging System
High-throughput batch and Kafka-based messaging system replacing legacy ETL workflows for large-scale customer notifications at PNC Bank.
- Solely designed and implemented the entire system end-to-end, from ingestion to delivery.
- Built a Spring Batch pipeline to read and process 4M+ records from SharePoint via Microsoft Graph API in parallel.
- Engineered concurrent API calls for customer phone retrieval and database inserts, optimizing I/O throughput.
- Integrated Kafka connectors to stream records directly from the database into topics for real-time processing.
- Developed a bulk messaging Kafka consumer capable of processing 4M+ records in 1.5 hours (legacy ETL: 100K in 2 hours; ~53× faster).
- Architected fault-tolerant job recovery and retry mechanisms ensuring data consistency across parallel tasks.
- Deployed and monitored the system on OpenShift, achieving a 7× performance improvement and sustained operational reliability.
SMS Banking Integrations
Modernized messaging services powering multi-channel customer notifications at PNC Bank.
- Handled 5k+ transactions per second with resilient Kafka consumer groups and short-circuiting patterns.
- Implemented OAuth2 security and observability standards across 50+ microservices.
- Reduced incident response time by 30% via Dynatrace dashboards and automated runbooks.
- Upgraded legacy applications from Java 8 → 17 → 21, leveraging language-level optimizations and improved GC tuning.
- Integrated Resilience4j circuit breakers and backoff policies to harden high-throughput pipelines and eliminate stop-the-world rebalances.
- Reduced cluster memory footprint by 200GB through autoscaling strategy design, resource tuning, and performance profiling.
Recipe AI Platform
Semantic recipe discovery engine with ingestion pipeline for 200k+ records and personalized search results.
- Processed 200k+ recipes via Spring Batch with automated data quality checks and validation rules.
- Developed scalable ingestion and enrichment pipelines using Spring Boot and PostgreSQL with pgvector for semantic search.
- Implemented embedding generation workflows using OpenAI and local models (BGE-base, Llama 3) for vector similarity ranking.
- Reduced search latency by 45% through vector indexing, caching, and optimized query strategies.
- Optimized AI cost by 30% via prompt tuning, token aggregation, and request batching.
- Designed RESTful APIs for semantic search, filtering, and recipe recommendations.
- Integrated Angular frontend for interactive, low-latency semantic exploration of recipes.
- Implemented batch failure logging and retry workflows for resilient large-scale data processing.
Experience
A track record of owning outcomes, mentoring teams, and elevating operations.
Software Engineer
PNC Bank · Remote
2022 — Present
- Delivered and maintained 50+ Java microservices handling 5k+ TPS for enterprise SMS banking.
- Solely designed and implemented a new bulk messaging platform using Spring Batch and Kafka, reducing end-to-end processing time from 7 hours to 1.5 hours while scaling to 4M+ records.
- Integrated Resilience4j circuit breakers to enhance fault tolerance and failover handling for high-throughput messaging pipelines.
- Analyzed cluster-wide resource usage and reduced total JVM and memory consumption by 200GB through autoscaling optimization, profiling, and performance analytics.
- Led the cloud migration of 15 legacy services to OpenShift with automated resilience and load testing pipelines.
- Improved customer onboarding by 25% by launching auto-enrollment and proactive messaging flows.
- Enhanced observability and incident response through Dynatrace dashboards, distributed tracing, and runbook automation.
- Adopted AI-assisted tools (Copilot, Codex) to streamline development, improve test coverage generation, and maintain consistent code documentation across Java and Python services.
Assistant Manager
The Libertine Pub · San Luis Obispo, CA
2021 — 2022
- Trained 90% of new staff on high-volume operations and guest experience standards.
- Cut waste by 10% through measurement systems and supplier process updates.
Operations Coordinator
The Litigation Practice Group · San Clemente, CA
2020 — 2021
- Boosted productivity by 30% via scheduling policies and daily standups.
- Improved customer outcomes by 15% through trend analysis and reporting.
Let's connect
I enjoy collaborating on backend-heavy products, data-driven experiences, and platform enablement. Reach out to talk about roles, projects, or mentoring.
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