Apache Kafka Engineer for Long-Term Remote Contract

@shadabkhan92

As a highly skilled and experienced Apache Kafka Engineer, I am uniquely qualified for this long-term remote contract project. For over 3 years, I have been actively engaged in administrating and developing with Apache Kafka in large-scale enterprise environments - a key requirement stated in your project description. I have deep expertise in designing, building, administering, and maintaining Kafka clusters across varying environments and ensuring their streamlined integration with microservices and API Gateways. One of the factors that distinguishes me from other candidates is my comprehensive proficiency in the Linux-based command-line administration, storing topics, partitions, brokers' performance, as well as high-level understanding of event-driven architectures. My skillset extends to include troubleshooting complex issues - a capability I believe can add immense value to any potential challenges your organization might be facing or provide proactive solutions before they even arise. Additionally, my background in CI/CD pipelines (Jenkins, GitLab CI), Docker, Kubernetes etc. lends itself to aligning perfectly with your needs for this project.

@mengw3

Hi - a long-term Kafka role is a strong fit. I've run Kafka event-streaming inside ESB and enterprise data-hub (data middle-platform) builds: topic/partition design, replication for HA, consumer groups, Kafka Connect, and pipelines feeding microservices. Application points: - Experience: Kafka cluster ops + Connect, event-driven architecture, Linux CLI, Docker/Kubernetes, Prometheus/Grafana monitoring. - Projects: (1) ESB integration layer routing high-volume events across systems via Kafka; (2) data-hub ingestion (CDC/stream) pipelines with schema management; (3) GCP/GKE data engineering with Kafka streaming + Airflow. - Availability: 40 hrs/week with daily overlap of your ICT hours; I accept the evaluation terms ($500 then $750-1000). Screening answers: 1) Scale: multi-broker clusters, replication factor 3, partitioned topics tuned for throughput and ordering; ACLs, retention and rebalancing managed. 2) Troubleshooting: rising consumer lag from rebalancing storms / under-replicated partitions - diagnosed via lag + JMX metrics, fixed with partition/consumer and broker-config tuning. 3) API Gateway: gateway -> Kafka ingest (REST proxy / Connect), events consumed by downstream microservices. Ready for the video interview + practical assessment. Profile: https://www.freelancer.com/u/mengw3

@mobasherreza10

As a highly skilled Software Developer and Cloud Architect with a focus on Data Processing and DevOps, I possess the technical expertise and robust experience that aligns closely with your requirements for an Apache Kafka Engineer. For over 3 years, I have been proficiently administering and developing Apache Kafka in diverse enterprise environments. Apart from managing Kafka clusters, topics, partitions, and data streaming pipelining, I have proven skills in integrating Kafka with microservices and API Gateways. My solid grasp of event-driven architectures also bolsters my contributions to reliable system integration. Operating effectively and efficiently on a remote basis comes naturally to me. My strong communication skills ensure seamless collaboration with colleague teams within different time-zones. Moreover, my familiarity with tools like Prometheus, Grafana, Docker, Kubernetes along with my CI/CD pipeline and Agile/Scrum experience give me an added advantage when it comes to ensuring operational efficiency.

@Dzimark

Hi, Apache Kafka clusters fail most often from under-provisioned partitioning and misconfigured retention/replication during scale. My first focus is validating topic partitioning, replication factors, and broker configs to prevent data loss and uneven consumer load. I have 5+ years working with Apache Kafka in production, operating clusters on both self-managed Linux servers and AWS MSK. I built event streaming pipelines connecting Kafka to microservices and API Gateways using Kafka clients in Java and Node.js, managed Kafka Schema Registry deployments, and implemented monitoring with Prometheus and Grafana. Relevant work includes migrating a legacy message bus to Kafka for a payments platform where I redesigned topics and partitioning to improve throughput by 3x and implemented disaster recovery with cross-region replication; building an event-driven order processing pipeline integrated with API Gateway and Dockerized microservices; and administering an MSK cluster with automated CI/CD broker config rollouts and alerting on ISR and under-replicated partitions. I start by running a targeted cluster health audit: broker configs, topic layouts, consumer group lags, ISR status, and retention settings, then deliver a prioritized remediation plan and implementation for capacity and DR. - Please include a brief summary of your Kafka experience, 2-3 specific Kafka projects, your current time zone and availability, confirmation of the compensation structure, and answers to screening questions I have 5+ years with Apache Kafka; projects: payments migration (self-managed), order processing pipeline (microservices + API Gateway), AWS MSK administration with Schema Registry and CI/CD. Time zone: IST (UTC+5:30). Availability: 20-30 hours/week and can expand for on-call windows. Compensation: I accept hourly or fixed contract; please confirm your budget range so I can align commitment and SLAs. - Do you want a short technical screening now or a scheduled call to review the cluster audit approach? Happy to hop on a brief call whenever it suits you. Dzimark

@rakhshanz3

As an accomplished Apache Kafka engineer with over 3 years of experience, I am well-versed in the full spectrum of tasks outlined within this project. My career trajectory spans from being a lecturer to leading the technical development as the CTO of an AI startup. This range of experiences has sharpened my problem-solving skills and deepened my proficiency in Kafka administration and development. To give you an idea of my expertise, I have developed and managed multiple Kafka clusters, with the largest scale consisting of 15 brokers, 250 topics, and a throughput of 200k messages per second. When it comes to troubleshooting, there was a complex issue where Kafka wasn't able to maintain the desired performance due to suboptimal network configuration. In response, I refined the network architecture and implemented client-side optimizations, ultimately increasing the throughput by 30%. Envisioning myself contributing to your enterprise-grade data streaming and event-driven architecture initiatives is an exciting opportunity that aligns with my technical competencies perfectly. I can bring my comprehensive understanding of Kafka's operational aspects, collaboration skills gained from working in Agile/Scrum environments, and exposure to CI/CD pipelines to ensure smooth integration with API Gateways and backend systems. Together, we can actualize stable yet adaptable Kafka frameworks that maximize your data processing capabilities. Let's get started in July!

@Jaydeep365

Hi, I have 9+ years of experience in backend development, Node.js, AWS, microservices, API integrations, Linux administration, Docker, Kubernetes, CI/CD, and scalable system architecture. My experience includes: *Building and maintaining microservices-based applications *Event-driven integrations and asynchronous processing *AWS infrastructure and cloud deployments *Docker, Kubernetes, and DevOps workflows *API Gateway and backend system integrations *Performance optimization and production troubleshooting While my primary expertise is backend architecture and distributed systems rather than dedicated Kafka administration, I am comfortable working with streaming architectures, microservices, Linux environments, and large-scale integrations. I am interested in discussing the project requirements and understanding the current Kafka environment. If my background aligns with your needs, let's connect for a technical discussion. Weekly Availability: 40+ hours Looking forward to your response. Thanks.