We’re looking for a candidate to fill this position in an exciting company. Working proactively and closely with other data platform engineers to developing and defining the architecture of their cloud-based data infrastructure, creating SLOs, improving monitoring and deployment process to serve their most data-intensive services; Work proactively with other cloud infrastructure teams to improve cloud practices and propose new solutions to enhance the quality of their batch and real-time data infrastructure; Contribute to design, coding, testing and debugging steps of the development cycle of Data tools and services to ensure low operational footprint, reliability, availability, and reproducibility of their cloud infrastructure. Build APIs, IaC and automation to control data-centred stateful infrastructure hosted on Kubernetes clusters as all final releases of their Data Infrastructure Services are backed on Kubernetes (100%). Enjoy working with complex business logic and deal with large scale to build low latency systems; Smart and creative, both, you have the ability and persistence to solve problems, big and small. Curious by nature, you’re constantly looking for ways to improve upon things; Demonstrate critical thinking and problem-solving capabilities both independently and collaboratively; You’re flexible, fearless, and excited to help build something; You’re hands-on, in the right ways; willing and able to do what’s needed, no matter the task. Experience as a Data, Software or Infrastructure engineer (data related) on realtime or event-driven applications. BS in Computer Science, Engineer (Software or others), Statistics, Physics or a related field; Experience with Python, Scala, Java, Shell or Go (at least two) for automation and system operations; Experience with at least one Realtime infrastructure (among Flink, Kafka, AWS Kinesis, Storm, Spark) or stateful event-driven services on Kubernetes (like Machine Learning APIs, Spark streaming, AKKA, Kafka Connect, Kafka stream); Developer experience using Docker and Kubernetes; Experience creating CI/CD processes; Experience using Terraform for IaC; Experience with cloud solutions and best practices on AWS (tagging, IAM for example); Practical knowledge on Network specification and operation, especially on AWS; Proven experience applying SRE practices (especially observability and automation). Plus Experience with orchestration frameworks like Apache Airflow; Developer Experience with Apache Beam, Kafka Connect, Kafka stream, Flink; Kubernetes Administration Certification (CKA); Experience developing or managing open-source NoSQL Databases (Cassandra, MongoDB, Redis, etc).
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