Hire Kafka Engineering
for real-time data streaming

From event-driven microservices and real-time analytics to change data capture and stream processing, our Kafka engineers build reliable, high-throughput data infrastructure.
Discuss your Kafka project
Kafka logo
20+
Kafka projects delivered
6+
years of Kafka expertise
30+
Kafka & data engineers
Core Capabilities
What we build with Kafka
Event-Driven Microservices Messaging
Decoupled and reliable
Event-driven microservices with Kafka as the central nervous system — reliable message delivery, exactly-once semantics, and decoupled services that scale independently.
Event-Driven Microservices
Kafka Streams Stream Processing
Real-time analytics
Real-time stream processing with Kafka Streams and ksqlDB — filtering, aggregating, joining, and transforming data streams with stateful processing and windowed computations.
Stream Processing
Kafka Connect Data Pipelines
Connect everything
Real-time data pipelines with Kafka Connect — CDC from databases, streaming to data warehouses, and integrating with Elasticsearch, S3, and cloud services without custom code.
Data Pipelines
How It Works
From architecture to production
Step 1
Architecture & Topology
Design
We evaluate your requirements and design the right Kafka architecture — whether it is event-driven microservices, real-time analytics pipelines, or change data capture from legacy databases.
Step 2
Agile
Development
Our enterprise solution engineers work in 2-week sprints with continuous integration and demo cycles. You see working infrastructure every step of the way.
Step 3
Testing &
CI/CD
Integration tests with embedded Kafka, schema registry validation, and consumer contract testing. Our QA specialists and DevOps engineers ensure every pipeline handles edge cases and failures gracefully.
Step 4
Deployment &
Monitoring
We deploy Kafka clusters on Kubernetes with Strimzi, or use managed services like Confluent Cloud and Amazon MSK. We configure monitoring with Prometheus, Grafana, and Kafka-specific alerting.
Hire Kafka Engineers

Kafka engineers ready to join your team

Boost your data infrastructure capacity with dedicated Kafka engineers who build reliable, high-throughput streaming systems from day one.

Hire Kafka Engineers
Event-driven microservices architecture
Kafka Streams & real-time processing
Kafka Connect & data pipeline design
Schema Registry & Avro/Protobuf
Cluster operations & performance tuning
Why product Enhancement
Improve with intent, not impulse
Generative AI
AI-assisted
code review
Every pull request is reviewed by AI tools that catch serialization issues, consumer group misconfigurations, and Kafka anti-patterns before human review begins.
AI testing icon
AI-powered
testing
Automated test generation for Kafka producers, consumers, and stream processors — increasing coverage while handling async messaging complexities.
Schema evolution icon
Schema
evolution
AI-driven schema compatibility analysis and migration planning — ensuring Avro and Protobuf schema changes don't break existing consumers.
Intelligent automation icon
Intelligent
automation
AI-driven partition rebalancing, consumer lag analysis, and throughput optimization — ensuring your Kafka infrastructure runs efficiently at any scale.
FAQ

Frequently Asked
Questions

Apache Kafka is a distributed event streaming platform for building real-time data pipelines and streaming applications. Use it when you need reliable, high-throughput messaging between microservices, real-time analytics, event sourcing, or change data capture.
Unlike traditional message queues that delete messages after consumption, Kafka retains messages for a configurable period. This enables multiple consumers to read the same data independently, replay events, and build event-sourced architectures.
Kafka Connect is a framework for streaming data between Kafka and external systems — databases, search indexes, file systems, and cloud services. We configure source and sink connectors to build real-time data pipelines without custom code.
Yes. Kafka is designed for massive scale — handling millions of messages per second with low latency. Companies like LinkedIn, Netflix, and Uber use Kafka to process trillions of messages daily. We design partition strategies and cluster topologies for your specific throughput requirements.
We set up monitoring with Prometheus and Grafana for broker health, consumer lag, partition distribution, and throughput metrics. We configure alerting on consumer lag spikes, under-replicated partitions, and broker failures for proactive incident response.
Docker
Terraform
DSi Kafka engineering team
LET'S CONNECT
Ready to scale your product?
Book a session to discuss your Kafka project with our engineering leadership.
Talk to the team