A shortlist typically within 72 hours, usually contributing inside two weeks, and 30-day replacement support if the fit is wrong (terms in your agreement).
Shortlist typically in 72 hours · 30-day replacement support · Month-to-month
Kafka often starts as a fix for one integration and becomes the backbone of the business. Then the questions start. Which topics are still used? Why does this consumer lag every morning? What happens if the same message is processed twice? Schemas change without warning and break downstream services.
A senior Kafka engineer designs topics, partitions and schemas deliberately, builds consumers that handle duplicates and failures, and keeps clusters healthy as volume grows.
Clear events, keys and ordering guarantees.
Idempotency, retries, dead-letter topics and offset handling.
Avro or Protobuf with Schema Registry and compatibility rules.
Kafka Streams, ksqlDB or Flink.
Debezium and connectors to databases and warehouses.
Monitoring lag, brokers and partitions.
Lost or duplicated data. Consumers without idempotency or proper offset handling produce wrong totals and double actions.
Growing lag. Poor partitioning and slow consumers delay everything downstream.
Breaking changes. Without schema governance, one producer change can break many consumers.
Every engineer we put forward has at least five years of hands-on experience. Within that, here is how the levels differ.
Senior Engineer (5–8 years). Builds producers and consumers in Java, Kotlin, Python or Go, works with Kafka Streams or ksqlDB, Kafka Connect and Schema Registry, and tunes partitions and consumer groups.
Lead / Architect (8+ years). Owns event-driven architecture, topic and schema governance, cluster sizing, multi-region design and platform operations on Confluent, MSK or self-managed Kafka.
Event-driven systems. Designing topics, events and consumers for new services
Kafka Connect pipelines. CDC from databases with Debezium and sinks to warehouses
Stream processing. Kafka Streams, ksqlDB or Flink for real-time aggregations
Cluster operations. Sizing, monitoring, upgrades and migration to Confluent Cloud or MSK
Week one. They map topics, consumers, schemas, lag and cluster health.
Weeks two and three. First fixes to the most problematic consumer or pipeline, with monitoring added.
Week four. A written plan for schema governance, scaling and reliability.
No schema registry. Schemas and compatibility rules prevent silent breakage.
Assuming exactly-once everywhere. Design consumers to be idempotent regardless of guarantees.
Too few or too many partitions. Partition counts should follow throughput and ordering needs.
Rates depend on seniority, scope and engagement length. See the cost guide for market ranges, or tell us the role and we will give you a firm number.
Tell us the role and we will typically send a shortlist within 72 hours.
Tell Us the RoleTell us the role. Three to five profiles, typically within 72 hours.