Real-Time Data Engineer

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. They are seeking an experienced Real-time Data Engineer to architect, deploy, and operate large-scale Apache Kafka and Confluent platform environments. The role involves owning the Kafka platform, collaborating with cross-functional teams, and ensuring a reliable streaming platform.

Responsibilities:

• Architect, deploy, and operate large-scale Apache Kafka and Confluent platform environments supporting mission-critical event-driven workloads
• Own the Kafka platform end-to-end, including cluster sizing, configuration, security, automation, observability, and developer enablement
• Partner with application teams to deliver a reliable, performant, and developer-friendly streaming platform
• Work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions
• Raise the bar through code review, design review, and mentorship of more junior engineers

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related technical discipline
• Five or more years of experience operating Apache Kafka or Confluent Platform in production
• Deep, hands-on knowledge of Kafka internals (partitions, replication, ISRs, consumer groups)
• Strong experience with Kafka security (SASL, mTLS, ACLs, RBAC)
• Hands-on experience with Kafka Connect, Schema Registry, and either Kafka Streams or ksqlDB
• Experience with HA/DR strategies for Kafka
• Strong scripting skills in Python, Bash, or Go
• Hands-on experience with infrastructure-as-code (Terraform, Ansible)
• Working knowledge of observability tooling for Kafka
• Excellent troubleshooting, communication, and documentation skills
• Confluent Certified Administrator or Developer credentials
• Experience operating Kafka on Kubernetes (Strimzi, Confluent Operator)
• Exposure to managed Kafka services (AWS MSK, Azure Event Hubs Kafka API)
• Familiarity with stream processing frameworks (Flink, Spark Streaming)
• Experience with data governance and lineage for streaming data