AWS EKS & Kafka Platform Lead Engineer
Ecloud Labs
6 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
SeniorJob location
Tech stack
Airflow
Amazon Web Services (AWS)
Apache HTTP Server
Performance Tuning
Data Processing
Data Storage Technologies
System Availability
Spark
Kubernetes Helm Charts
Build Management
Data Lake
Kubernetes
Infrastructure Automation Frameworks
Apache Flink
Kafka
Terraform
Apache Beam
Amazon Web Services (AWS)
Confluent
Job description
What You''''ll Do As a lead member of our team, you''''ll focus on designing, deploying, and maintaining our core streaming and orchestration platforms. This is a hands-on leadership role.
- Lead the setup, configuration, and ongoing management of Kubernetes clusters on AWS EKS, ensuring high availability and performance for data workloads.
- Design Apache Kafka operations at massive scale: create and manage topics, scale nodes/brokers, implement tagging/classification, tune for 1M+ records/second throughput, and handle petabyte-level storage.
- Deploy Kafka using modern tools like Strimzi (Kafka operator for Kubernetes), Confluent components, and Helm charts.
- Design and build integration and orchestration with tools such as Apache Spark, Airflow, Apache Beam, and emerging Flink pipelines for batch and streaming workloads.
- Contribute to building and enhancing our Data Lake and Data Mesh architecture, incorporating open table formats like Apache Iceberg for reliable, versioned data storage.
- Collaborate with data engineers and application teams to provision resources, troubleshoot issues, and implement best practices for observability, security, and cost efficiency.
- Automate infrastructure and deployments using IaC principles (e.g., Helm, Terraform where applicable) to enable self-service for teams.
Requirements
- You''''re a hands-on architect who can delegate, director, and mentor other talented team members.
- Strong primary expertise in AWS, especially EKS (Kubernetes cluster management).
- Solid production experience with Apache Kafka at scale-topic creation/management, cluster scaling, performance tuning, and related ecosystem tools.
- Familiarity with Kafka deployment on Kubernetes via Strimzi, Confluent, or Helm.
- Working knowledge of related data processing tools: Spark, Airflow, Apache Beam, and ideally exposure to Flink or similar streaming engines.
- Experience or interest in modern data lake technologies like Apache Iceberg, Data Lake / Data Mesh patterns.
- Comfortable in a mixed on-prem and cloud (AWS) environment.
- Strong problem-solving skills, attention to detail, and a collaborative mindset.
If you''''re excited about high-throughput streaming on AWS EKS, Kubernetes-native platforms, and contributing to a growing Data Mesh/Data Lake initiative-while enjoying great perks and a balanced lifestyle-we''''d love to hear from you!
About the company
We''''re architecting and building a modern, high-scale data platform to power real-time analytics and a next-generation Data Lake / Data Mesh architecture. Our environment handles massive throughput with Kafka processing over 1 million records per second and petabytes of total data, running on AWS EKS (Kubernetes) with a mix of on-prem and cloud components.
Join in a leadership role on a collaborative team where your work directly enables cutting-edge data streaming and processing. We value people who like to get their hands dirty and keep their skills sharp.
Perks
* Free GrubHub food deliveries to keep you fueled
* Free downtown parking
* Frequent team parties every 2 weeks - we celebrate wins and enjoy time together
* Work on high-impact, large-scale systems without after-hours support demands
* Opportunity to contribute to evolving initiatives like Data Lake, Data Mesh, Apache Iceberg, and real-time processing pipelines