<p>We are seeking a highly skilled and self-motivated Senior Embedded DevOps Engineer to support our data teams. This role will focus on driving changes and ensuring adherence to company-established standards for data infrastructure and CI/CD pipelines. The ideal candidate will have strong experience working with AWS and/or GCP, cloud-based data streaming and processing services, containerized application deployments, infrastructure automation, and Site Reliability Engineering (SRE) best practices for performance and cost optimization.</p> <p>What You'll do:</p> <ul> <li>Drive initiatives to implement and enforce best practices for data streaming, processing, analytics and monitoring infrastructure. </li><li>Deploy and manage services on Kubernetes-based platforms such as Amazon EKS and Google Kubernetes Engine (GKE). </li><li>Provision and manage cloud infrastructure using Terraform, ensuring best practices in security, scalability, and cost-efficiency. </li><li>Maintain and optimize CI/CD pipelines using Jenkins, ArgoCD, and GitHub Enterprise Actions to support automated deployments and testing. </li><li>Work with cloud-native data services such as AWS Kinesis, AWS Glue, Google Dataflow, and Google Pub/Sub, BigQuery, BigTable </li><li>Familiarity with workflow orchestration services such as Apache Airflow and Google Cloud Composer. </li><li>Develop and maintain automation scripts and tooling using Python to support DevOps processes. </li><li>Monitor system performance, troubleshoot issues, and implement proactive solutions to enhance reliability and efficiency. </li><li>Implement SRE practices to improve service reliability, scalability, and cost-effectiveness. </li><li>Analyze and optimize cloud costs, identifying areas for improvement and implementing cost-saving strategies. </li><li>Ensure compliance with security policies and best practices in cloud environments. </li><li>Drive adoption of company standards and influence data teams to align with best DevOps and SRE practices. </li><li>Collaborate with cross-functional teams to improve development workflows and infrastructure. </li></ul> <p>What you bring:</p> <ul> <li>7+ years of experience in a DevOps, Site Reliability Engineering, or Cloud Infrastructure role. </li><li>Strong experience with AWS and GCP data services, including Kinesis, Glue, Pub/Sub, and Dataflow. </li><li>Proficiency in deploying and managing workloads on Kubernetes (EKS/GKE) in production environments. </li><li>Hands-on experience with Infrastructure-as-Code (IaC) using Terraform. </li><li>Expertise in CI/CD pipeline management using Jenkins, Argo-CD, and GitHub Enterprise Actions. </li><li>Programming skills in Python for automation and scripting. </li><li>Experience with observability and monitoring tools (e.g., Prometheus, Grafana, Datadog, or CloudWatch). </li><li>Strong understanding of SRE principles, including performance monitoring, incident response, and reliability engineering. </li><li>Experience with cost optimization strategies for cloud infrastructure. </li><li>Self-motivated and driven, with a strong ability to influence and drive changes across multiple teams. </li><li>Ability to work collaboratively in an agile environment and support multiple teams. </li><li>Experience with data lake architectures and big data processing frameworks (e.g., Apache Spark, Flink, Snowflake, BigQuery). </li><li>Familiarity with event-driven architectures and message queues (e.g., Kafka, RabbitMQ). </li><li>Experience with workflow orchestration tools such as Apache Airflow and Google Cloud Composer. </li><li>Knowledge of service mesh technologies like Istio. </li><li>Experience with GitOps workflows and Kubernetes-native tooling. </li></ul> <p>#LI-SK</p> <p>#LI-Hybrid</p>