SSE - Kafka Developer

Experience Required

10+ years overall, with 5+ years in Kafka-based data streaming development.
Must have delivered production-grade Kafka pipelines integrated with real-time data sources and downstream analytics platforms.

Overview

We are looking for a Kafka Developer to design and implement real-time data ingestion pipelines using Apache Kafka. The role involves integrating with upstream flow record sources, transforming and validating data, and streaming it into a centralized data lake for analytics and operational intelligence.

Role & responsibilities

• Develop Kafka producers to ingest flow records from upstream systems such as flow record exporters (e.g., IPFIX-compatible probes).
• Build Kafka consumers to stream data into Spark Structured Streaming jobs and downstream data lakes.
• Define and manage Kafka topic schemas using Avro and Schema Registry for schema evolution.
• Implement message serialization, transformation, enrichment, and validation logic within the streaming pipeline.
• Ensure exactly once processing, checkpointing, and fault tolerance in streaming jobs.
• Integrate with downstream systems such as HDFS or Parquet-based data lakes, ensuring compatibility with ingestion standards.
• Collaborate with Kafka administrators to align topic configurations, retention policies, and security protocols.
• Participate in code reviews, unit testing, and performance tuning to ensure high-quality deliverables.
• Document pipeline architecture, data flow logic, and operational procedures for handover and support.

Preferred candidate profile

• Proven experience in developing Kafka producers and consumers for real-time data ingestion pipelines.
• Strong hands-on expertise in Apache Kafka, Kafka Connect, Kafka Streams, and Schema Registry.
• Proficiency in Apache Spark (Structured Streaming) for real-time data transformation and enrichment.
• Solid understanding of IPFIX, NetFlow, and network flow data formats; experience integrating with nProbe Cento is a plus.
• Experience with Avro, JSON, or Protobuf for message serialization and schema evolution.
• Familiarity with Cloudera Data Platform components such as HDFS, Hive, YARN, and Knox.
• Experience integrating Kafka pipelines with data lakes or warehouses using Parquet or Delta formats.
• Strong programming skills in Scala, Java, or Python for stream processing and data engineering tasks.
• Knowledge of Kafka security protocols including TLS/SSL, Kerberos, and access control via Apache Ranger.
• Experience with monitoring and logging tools such as Prometheus, Grafana, and Splunk.
• Understanding of CI/CD pipelines, Git-based workflows, and containerization (Docker/Kubernetes)