• De-fragmented the company’s eventing architecture by consolidating 3 legacy platforms into a single, high-throughput unified system on Kafka. Eliminated data sprawl and cross-team friction by pioneering a schema-first governance model, resulting in a 99.9% reduction in downstream data corruption and standardized event production across 50+ microservices

• Architected a Data Privacy Engine that dynamically redacts PII across the eventing platform, mitigating compliance risks. Partnered with Security to implement a semantic data classification system, enabling 100% automated mapping of user-defined data types to global privacy policies for 20+ downstream consumers

• Steered the Infrastructure squad as Tech Lead, orchestrating a multi-quarter roadmap and partnering with Product to define technical boundaries leveraging deep domain expertise to advocate for the customer perspective

• Pioneered Block’s Customer Data Platform (CDP), architecting Ingestion and Router services to process 1B+ daily messages. Engineered a distributed Pub/Sub architecture for real-time synchronization across Amplitude, Iterable, and 5+ internal sinks, maintaining sub-second latency and high fault tolerance at scale

• Architected a high-throughput data pipeline to sync 3TB of daily CDP messages to Snowflake. Optimized infrastructure spend by implementing an hourly aggregation and automated ingestion strategy, ensuring high data availability for mission-critical business reporting and enterprise ETL workflows

Analytics Platform team at Ericsson MediaFirst

Deployment

• Used SaltStack to automate deployment and configuration of analytics infrastructure including: Kafka, Zookeeper, Mesosphere, Logstash, Elasticsearch, and Zabbix

• Over 20 trial/production environments were deployed without manual steps in Azure cloud and Openstack

Realtime Streaming Data Pipeline

• Built platform instrumentation library in C# used by every service for aggregating performance counters and flushing logs/counters to multiple sinks including Kafka and a rotating local file

• Integrated Logstash to forward logs from Kafka to Elasticsearch/Kibana for visualization

C# Services and Workers

• Delivered Analytics Collection Service to serve as public endpoint for external clients to send their logs into the data pipeline. This service writes logs to Kafka and large datasets to blob storage

• Built Analytics Collection Worker to validate different types of logs in Kafka against its respective schema to prevent forwarding conflicting field mappings to backend data stores. Validation happens offline instead of at the collection service to reduce client latency awaiting acknowledgment from collection service

• Implemented Monitoring worker to do discovery on expected service instances and check for matching service heartbeats. Service center relies on alerts from this worker to detect stopped services

• Wrote customer-facing controllers in OSS Proxy (Operations Support System) to manage data retrieval from Analytics data stores.