✓
🎬 Intro
View profile
Looking to hire a Kafka engineer or consultant? RemoteAI connects you directly with vetted Kafka specialists — available dedicated full-time or as remote contractors — for Confluent Cloud deployments, event streaming architecture, Kafka Connect integrations, and real-time data pipeline development.
Describe your need. Write your own job post or generate one with AI, then filter talent profiles.
Chat, interview, and hire quickly so you can meet the freelancer you're excited about working with.
Message or video call, share files, and track project progress right from the platform.
Unlike Upwork or Toptal, RemoteAI takes zero commission when you hire. Agree terms directly with your talent. Ready-made services show their small service fee up front.
Looking to hire a Kafka engineer or consultant? RemoteAI connects you directly with vetted Kafka specialists — available dedicated full-time or as remote contractors — for Confluent Cloud deployments, event streaming architecture, Kafka Connect integrations, and real-time data pipeline development.
Kafka engineers design and operate distributed event streaming platforms that move data between systems in real time. They configure Kafka clusters (on-prem or Confluent Cloud / MSK / Confluent on GCP), design topic schemas and partitioning strategies, build connectors with Kafka Connect, implement stream processing with Kafka Streams or KSQL, and integrate Kafka with downstream systems like Spark, Flink, Snowflake, and ML feature stores. They manage consumer group lag, replication, retention, and schema registry for robust, at-scale event pipelines.
Finding the right apache kafka engineer requires more than evaluating technical skills — it means identifying someone who ships production-ready work and understands your business goals. Here is exactly how to do it.
Kafka is used for event sourcing, microservice integration, real-time analytics, CDC (Change Data Capture), and ML feature pipelines. Knowing your use case helps identify engineers with the right integration experience.
Ask about their experience with partition count decisions, replication factor tradeoffs, and how they have tuned producer and consumer configurations for high-throughput workloads.
Kafka in production requires monitoring consumer lag, managing disk retention, handling broker failures, and upgrading clusters without downtime. Ask for examples of production incidents they have resolved.
Streaming a change data capture feed from your database into Kafka is a common, high-value first project — it establishes the infrastructure foundation and demonstrates their end-to-end integration skills.
Apache Kafka Engineers on RemoteAI charge based on project scope and experience level. The following ranges reflect typical engagements for each type of project.
Use Kafka when you need durable event log semantics (replay events, multiple consumers reading independently), high throughput, or stream processing capabilities. Use SQS or RabbitMQ for simpler task queue patterns where event replay and stream processing are not needed.
Mid-level Kafka engineers charge $90–$150/hr. Senior engineers with high-throughput cluster design and cross-region replication experience charge $150–$240/hr.
Confluent Cloud is a fully managed Kafka service that eliminates cluster management overhead. AWS MSK and Google Cloud Pub/Sub offer similar managed options. For most companies without dedicated platform teams, managed Kafka significantly reduces operational risk.
No — Kafka is an event log, not a queryable database. Use Kafka to move data between systems and for event sourcing. Use a database or data warehouse for queryable storage. Many architectures combine both: Kafka for ingestion, a database or Snowflake for analytics.
Kafka enables real-time feature computation — streaming events are processed and written to a feature store (Redis, Feast) that the ML model reads at inference time. This is how production recommendation and fraud detection systems achieve real-time personalization.