About the service
I design and build real-time pipelines that move your business from nightly batch exports to live event streams. At the core is Apache Kafka as a reliable and high-performance data ingestion bus, and on top I connect Flink or Spark Streaming where stateful processing is needed: windowed aggregations, stream joins, complex event detection. As a result data arrives, is processed and reaches your data warehouse or dashboards in seconds, not hours, and your team stops waiting for the morning report — they respond to what's happening right now.
I lead the task from start to finish. I set up event ingestion from your applications, databases and third-party systems, connect the necessary connectors so change data capture, logs and clicks flow in cleanly and without loss. I define schemas and bring up a schema registry so producers and consumers don't break each other silently. I choose partitioning, retention period and consumer groups for your actual load. Where correctness matters, I implement exactly-once delivery through idempotent producers and transactional writes — retries won't turn into duplicate charges or doubled metrics.
Just as important is that the pipeline becomes manageable and reliable in production. I add monitoring of latency and throughput, alerts on consumer lag, dead letter queues and clear instructions so the on-call engineer knows exactly what to do at 3 AM. I document the topology, deliver infrastructure as code and walk your team through the system so you're not locked in to me. Anti-fraud, live analytics, device telemetry or an event bus between services — I deliver a pipeline that's fast, observable and truly ready for battle.
What typically goes into the work:
— Kafka cluster design: topics, partitioning and retention for your load
— Connectors and change capture from databases, applications and external services
— Stream processing in Flink or Spark Streaming: windows, joins, state
— Exactly-once guarantee, dead letter handling, monitoring and alerts
I lead the task from start to finish. I set up event ingestion from your applications, databases and third-party systems, connect the necessary connectors so change data capture, logs and clicks flow in cleanly and without loss. I define schemas and bring up a schema registry so producers and consumers don't break each other silently. I choose partitioning, retention period and consumer groups for your actual load. Where correctness matters, I implement exactly-once delivery through idempotent producers and transactional writes — retries won't turn into duplicate charges or doubled metrics.
Just as important is that the pipeline becomes manageable and reliable in production. I add monitoring of latency and throughput, alerts on consumer lag, dead letter queues and clear instructions so the on-call engineer knows exactly what to do at 3 AM. I document the topology, deliver infrastructure as code and walk your team through the system so you're not locked in to me. Anti-fraud, live analytics, device telemetry or an event bus between services — I deliver a pipeline that's fast, observable and truly ready for battle.
What typically goes into the work:
— Kafka cluster design: topics, partitioning and retention for your load
— Connectors and change capture from databases, applications and external services
— Stream processing in Flink or Spark Streaming: windows, joins, state
— Exactly-once guarantee, dead letter handling, monitoring and alerts
