Maintain and enhance Cloudera, Elastic Stack, and Dataiku platforms; develop data pipelines, streaming solutions, dashboards, integrations, and ML deployments. Automate infrastructure and CI/CD processes, troubleshoot platform issues, provide user support and training, and create reusable technical documentation. The role requires strong experience with data platforms, Hadoop ecosystem technologies, Python or Scala, REST APIs, ETL, infrastructure automation, and enterprise analytics environments.
Cloudera, Elastic Stack & DataikuPosition Overview
Key Responsibilities
RequirementsRequired Skills and Experience
Preferred Qualifications
Expected Outcomes
We are looking for an experienced Platform Engineer to support, maintain and further develop our Cloudera, Elastic Stack and Dataiku platform environment.
The role combines platform operations, solution development, automation and user support. You will work closely with data engineers, data scientists, analysts and business stakeholders to deliver stable, scalable and efficient data and analytics solutions.
Key Responsibilities
- Support, maintain and optimise Cloudera, Elastic Stack and Dataiku platforms
- Design and develop data pipelines, workflows, dashboards and platform integrations
- Build and support real-time streaming solutions using Apache Kafka
- Develop custom scripts, plugins and integrations using Python, Scala and REST APIs
- Design and automate ETL and data ingestion processes using tools such as Apache NiFi and Logstash
- Create Kibana dashboards, reports, queries and search solutions
- Support the deployment and operationalisation of machine learning models in Dataiku
- Automate platform deployments and operations using Ansible, Terraform or similar tools
- Implement CI/CD pipelines using GitHub Actions, Jenkins or comparable technologies
- Troubleshoot platform, workflow and integration issues
- Create reusable scripts, templates, libraries and technical documentation
- Provide guidance, training and platform support to users and internal teams
- Support occasional weekend or public holiday activities related to system changes or testing
RequirementsRequired Skills and Experience
- Strong experience with at least two of the following platforms:
- Cloudera
- Elastic Stack
- Dataiku DSS
- Good knowledge of Hadoop ecosystem technologies such as HDFS, YARN, Hive, Spark and Kafka
- Experience with Elasticsearch, Logstash, Kibana and Beats
- Experience designing data pipelines, ETL processes and streaming solutions
- Programming or scripting experience with Python and/or Scala
- Experience integrating platforms and external systems through REST APIs
- Good knowledge of GitHub, branching strategies, pull requests and code reviews
- Experience with CI/CD, infrastructure automation and deployment processes
- Understanding of clean code, secure coding and documentation standards
- Strong troubleshooting, analytical and communication skills
- Ability to translate business requirements into practical technical solutions
- Professional English skills
Preferred Qualifications
- Experience with machine learning deployment and data science platforms
- Knowledge of Apache NiFi, Terraform, Ansible or Puppet
- Experience working in enterprise-scale data and analytics environments
- Familiarity with agile and DevOps working practices
- Workload: 100%
- Start Date: As soon as possible
- Location: Flexible, with availability during Swiss working hours
Expected Outcomes
- Stable and well-maintained platform environments
- Reliable delivery of data pipelines, dashboards and analytics solutions
- Automated and optimised platform operations
- Effective user support and knowledge transfer
- Clear, reusable and up-to-date technical documentation
Similar Jobs
Financial Services
Build and maintain reusable Terraform modules for cloud database platforms across AWS and GCP. Develop Python automation, validations, testing, documentation, CI/CD workflows, security guardrails, and developer-experience tooling. Partner with application, security, risk, and compliance teams to create composable, well-documented infrastructure patterns with sane defaults. Improve module reliability and operability while expanding multi-cloud coverage.
Top Skills:
AuroraAWSDockerDynamoDBElasticacheGCPGitGoKmsKubernetesPre-CommitPythonRdsTerraformTerratest
Fintech • Mobile • Payments • Software • Financial Services
Build and evolve Wise’s scalable compute platform, enabling engineers to deploy and manage services reliably. Responsibilities include architecting infrastructure, automating AWS and application workflows, improving system scalability and resilience, advancing Kubernetes and service mesh capabilities, and leading technical projects while mentoring peers.
Top Skills:
AWSKubernetesKubernetes OperatorsService Mesh
Fintech • Mobile • Payments • Software • Financial Services
Build Wise’s production ML platform for financial crime detection. Responsibilities include designing declarative training pipelines, model packaging and serving abstractions, evaluation frameworks, monitoring and drift detection, automated retraining, audit trails, and integration with central ML infrastructure. The role focuses on improving data scientist productivity through reliable, scalable, standardized tooling and requires strong software engineering and end-to-end ML lifecycle expertise.
Top Skills:
AirflowJavaKotlinKubeflowMlflowOnnxPythonSQL
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.


