Kafka Engineer

Kafka Engineer

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications. As we continue to grow, we're looking for a skilled Kafka Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Kafka Engineer Job Title: Kafka Engineer

Location: 100% Remote (Continental United States)

Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)

Salary: $100K - $150K / Annum

Experience: 5+ years

Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.

Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)

Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap

Compensation: Competitive base salary commensurate with experience, plus benefits.

This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies. This role is part of Bright Vision Technologies' in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved. We do not engage in C2C, 1099, or third-party arrangements for this role. Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables. No new H1B sponsorship is available for this role. However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates. For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.

Job Summary

We are seeking an experienced Kafka Engineer to architect, deploy, and operate large-scale Apache Kafka and Confluent platform environments supporting mission-critical event-driven workloads. In this role you will own the Kafka platform end-to-end, including cluster sizing, configuration, security, automation, observability, and developer enablement. The ideal candidate will combine deep Kafka internals knowledge with strong DevOps and SRE practices, and will partner with application teams to deliver a reliable, performant, and developer-friendly streaming platform. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.

Key Responsibilities

• Architect, deploy, and operate large-scale Apache Kafka or Confluent Platform clusters across on-prem and cloud environments.
• Design partitioning, replication, and topic strategies that balance throughput, durability, and operational simplicity.
• Implement strong security on Kafka clusters using SASL, mTLS, ACLs, RBAC, and integration with corporate IdPs.
• Operate Schema Registry, Kafka Connect, KSQL/ksqlDB, and Kafka Streams in production.
• Build and operate Kafka Connect pipelines integrating sources and sinks across enterprise systems.
• Design HA/DR strategies for Kafka, including MirrorMaker 2, Cluster Linking, and multi-region active-active patterns.
• Build CI/CD pipelines for Kafka topic, ACL, and connector configurations using GitOps patterns.
• Implement comprehensive observability using Prometheus, Grafana, Datadog, or Confluent Control Center.
• Drive Kafka cost and capacity optimization through right-sizing and storage tiering.
• Onboard application teams to Kafka with clear patterns, templates, and best practices.
• Lead incident response and post-incident reviews for streaming workloads, applying disciplined engineering practices and partnering closely with stakeholders to ensure outcomes are durable, well-documented, and aligned with broader team and platform standards.
• Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time.
• Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
• Continuously evaluate emerging streaming technologies (Pulsar, Redpanda, AWS MSK, Azure Event Hubs).

Required Qualifications

• 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.

Preferred Qualifications

• 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.