Henri Idrovo

Spearheaded onboarding of new external client for real-time data ingestion pipeline where messages are read

from and written to Apache Kafka topics. Conducted stakeholder meetings to gather requirements and design

specifications, resulting in secure, seamless implementation deployed to production within four weeks, while

maintaining simplicity for existing users.

Identified and resolved software bottleneck in high-value transaction API by implementing asynchronous

programming, reducing response times by 20%, and exceeding critical Service Level Agreements, leading to

increased client satisfaction.

Engineered and optimized high-efficiency Java Spring API managing over 100,000 daily requests, ensuring

rapid response times (400ms) and robust scalability for critical financial transactions, deployed on AWS ECS

across two regions with continuous activity monitoring via Splunk and production alerts managed through

PagerDuty.

Championed rigorous code review practices across team, performing integration testing in pre-production

environments, which cut bug occurrences by 50% and guaranteed deployment of high-quality features;

communicated development progress consistently to key stakeholders, maintaining project transparency.

Built and refined Java Spring Boot APIs to serve JSON data from PostgreSQL database to internal clients,

ensuring high availability and streamlined data access for internal operations.

Developed and optimized Spring Integration ETL applications for ingesting hundreds of gigabytes of data per

day from multiple Apache Kafka topics, guaranteeing efficient and accurate data processing at scale.

Architected and deployed new streaming data pipeline systems using Apache Flink, Kafka, and Cassandra,

executing successful production launches that bolstered data processing capabilities and operational efficiency.

Directed maintenance of complex Apache Spark applications in Java and Python, managing data ingestion

pipelines that processed hundreds of gigabytes of traffic daily, ensuring system stability and performance

integrity.

Led team of junior engineers, addressing concerns about workload and delivery timelines by organizing

retrospectives and proposing new feature development processes, resulting in stakeholder alignment and timely

delivery of bug-free features; orchestrated requirement gathering, debugging methods and internal

communication, and outcome-driven development.

Managed production incident involving non-responsive database layer by investigating infrastructure logs and

identifying server capacity issues, leading to successful scaling of infrastructure and increased application load

capacity.

Designed and deployed Hadoop MapReduce ETL workflows for 3D building data ingestion, hosted on AWS with

performance metrics and reports persistently stored in S3, supporting delivery of high-quality geospatial data

solutions.

Oversaw and executed production deployments across AWS resources, including EMR, EC2, and S3, ensuring

smooth operations and compliance with cloud performance standards.