Platform & Data Infrastructure architect with 12+ years of
experience scaling distributed systems, orchestration and
streaming platforms, cloud infrastructure, and ML systems
Sr Staff Software Engineer
Affirm
Tech Lead, Batch & Streaming Data
Platforms
— Led core data infrastructure teams serving
~1000 engineers. Owned strategy and
cross-functional alignment for Kafka, Spark,
Temporal, Airflow, Flink
Established company-wide paved
paths, design constraints &
guardrails for safe, scalable
platform adoption.
Stepped into management
calibration; reviewed promo
packets and drove multiple
Junior to Staff-level
promotions
Reduced team
on-call load by 50% via
self-serve automation and
leadership accountability
reporting
Overhauled company-wide System
Design interview template for
consistent, higher-signal
evaluation
Temporal Platform — Designed, secured
VP + eng-lead alignment, and delivered
production-grade Temporal platform to GA,
powering stateful, durable Agentic/LLM
harnesses and Capital pipelines
Kubernetes Migration — Designed & led
cutover of 2000+ critical jobs to 17 EKS
clusters, peak 500TiB memory. Reduced env
provisioning (2 months to 1 week),
standardizing DevEx, 50% faster deploys
Platform Reliability & Risk
Mitigation
Architected usea1→usea2
multi-region deployment
for financial pipelines for EC2
control plane redundancy
Built a data-quality platform
that blocks pipeline
regressions,
safeguarding billions
from financial
discrepancies.
Designed a
SLA tracking system to
ensure platform and financial
pipelines are meeting
contractual SLAs
Platform Modernization & Cost
Efficiency
Luigi and Celery → Temporal:
Org alignment, designed adapter
for zero-code migrations.
Dramatically improving
reliability, o11y, and developer
velocity.
Presented at Replay 2026
Kinesis → Kafka: Managed
project and designed
zero-data-loss Kafka consumer
cutover.
$3M/year savings
Automated detection of
over-provisioned Spark
workloads.
$2M/year savings
Search Suggest + ML — Led
re-architecture of autocomplete ranking with
new ML platform and xgboost classifier for
contextual filters. Improved click-through
rate while maintaining low latency.
Realtime ML model for Store Visits —
Improved Flink app throughput by >1000
msgs/sec for online ML model classifying
customer visits from location pings.
Featured at
Flink Forward 2019
Chain Detection — Built Spark + ML
system to detect retail chains at scale.
Presented at PyBay 2018
Previous Roles
Software Engineer Intern, Yelp (Jun 2013 –
Aug 2013, San Francisco)
Software Engineer Intern, Marin Software
(May 2012 – Aug 2013, San Francisco)
Research Assistant, Computational
Linguistics Group (Sep 2013 – Jun 2014,
Univ. of Toronto)