• Architect, develop, and manage the data platform to support efficient data ingestion, transformation, quality assurance, monitoring, and accessibility • Collaborate closely with cross-functional teams to understand data needs

Role Description 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 Qualifications - 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 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

• Design and implement distributed scheduling and workflow systems • Improve job prioritization, resource allocation, and orchestration across hybrid environments • Build scalable, reliable platform services and storage abstractions • Lead complex projects from design through production delivery • Improve system reliability, observability, and operational performance • Provide technical leadership and mentorship across the team • Lead complex projects from start to finish, which includes gathering project requirements, translating them into a rational software design, reasoning effectively about supporting or dependent technologies, and communicating effectively with collaborators and teammates • Provide technical guidance to engineering and research staff • Mentor and grow individual contributors to continuously up-level the team

• Lead a platform engineering team: technical direction, design reviews, code review, and day-to-day delivery. • Set the technical direction for your team’s area of the stack. • Represent platform engineering in roadmap planning: translate product requirements into scoped, sequenced technical work. • Work closely with the bring-up team to surface operational pain points. • Collaborate with the security engineering team to integrate security guidance at the platform layer. • Coordinate with the other platform engineering leads on shared architecture, joint initiatives and cross-team delivery. • Own reliability, observability, security, and interface and versioning standards for the services your team ships. • Stay hands-on: take on complex or high-risk engineering work directly alongside the team. • Run post-mortems and close structural gaps after incidents. • Manage the team: 1:1s, performance conversations, hiring interviews and onboarding.