Platform Engineer

The role of Platform Engineer at Cloudera, Elastic Stack & Dataiku involves supporting, maintaining, and enhancing the company's platform environment. The company specializes in data and analytics solutions, leveraging technologies like Cloudera, Elastic Stack, and Dataiku. The Platform Engineer will work closely with various teams, including data engineers, data scientists, and business stakeholders, to ensure the delivery of stable, scalable, and efficient data solutions. The main day-to-day responsibilities include supporting and optimizing the Cloudera, Elastic Stack, and Dataiku platforms. This involves designing and developing data pipelines, workflows, and dashboards, as well as building real-time streaming solutions using Apache Kafka. The role also requires creating custom scripts, plugins, and integrations using Python, Scala, and REST APIs, and automating ETL and data ingestion processes with tools like Apache NiFi and Logstash. Additionally, the engineer will support the deployment of machine learning models in Dataiku and automate platform operations using tools like Ansible and Terraform. To excel in this role, candidates must have strong experience with at least two of the following platforms: Cloudera, Elastic Stack, and Dataiku DSS. They should also have a good understanding of the Hadoop ecosystem, including technologies like HDFS, YARN, Hive, Spark, and Kafka. Experience with Elasticsearch, Logstash, Kibana, and Beats, as well as designing data pipelines, ETL processes, and streaming solutions, is essential. Programming or scripting experience with Python and/or Scala, and the ability to integrate platforms and external systems through REST APIs, are also required. Additionally, candidates must have a strong knowledge of GitHub, branching strategies, pull requests, and code reviews, as well as experience with CI/CD, infrastructure automation, and deployment processes. Nice-to-have skills include experience with machine learning deployment and data science platforms, knowledge of Apache NiFi, Terraform, Ansible, or Puppet, and familiarity with enterprise-scale data and analytics environments. Experience working in agile and DevOps environments is also beneficial. The role offers flexible working conditions with the ability to work from anywhere, as long as the engineer is available during Swiss working hours. The team is supportive, and the role provides opportunities for growth and development. What the role asks for: - Experience with at least two of the following platforms: Cloudera, Elastic Stack, Dataiku DSS - Knowledge in the Hadoop ecosystem, including HDFS, YARN, Hive, Spark and Kafka - Experience with Elasticsearch, Logstash, Kibana and Beats - Experience in the design of data pipelines, ETL processes and streaming solutions - Programming or scripting experience with Python and/or Scala - Experience in the integration of platforms and external systems via REST-APIs - Good knowledge of GitHub, branching strategies, pull requests and code reviews - Experience with CI/CD, infrastructure automation and deployment processes - Ability to translate business requirements into practical technical solutions - Professional English skills