Description
We're looking for a talented Data Platform Engineer to join our team. As a Data Platform Engineer, you will lead the design and implementation of our cloud-native Warehouse and Machine Learning platforms, ensuring they are robust, secure, and scalable.
Key responsibilities include: Building for Scale: You will lead the design and implementation of our cloud-native Warehouse and Machine Learning platforms, ensuring they are robust, secure, and scalable. Mastering the Orchestration: You’ll dive deep into Kubernetes, leveraging Operators and Helm to automate complex data workflows and platform management. Building out kube native data and AI architecture. Bridging the Clouds: You will improve our existing tooling and implement new, seamless integrations between our AWS and GCP environments. Defining our State: You’ll use Terraform to manage and define our entire data infrastructure through code, ensuring reproducibility and transparency across the stack.
Requirements: K8s Expertise: You have a solid understanding and practical experience with Kubernetes, specifically working with Operators and Helm to manage complex application lifecycles. The Engineer's Mindset: You are proficient in Python or Java and enjoy writing clean, efficient code to solve infrastructure challenges. Cloud Native: You are comfortable working in at least one of the major cloud providers (AWS or GCP) and understand how to get the best out of their managed services. Optimising and refine: current data infrastructure, and deploying greenfield kube native OSS projects
Bonus points if you have: Experience with SQL-based transformation workflows, specifically using dbt within BigQuery. Familiarity with streaming and ingestion tech like Kafka or Debezium. A background in Linux administration or data management best practices.
Interview process: Interviewing is a two-way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general, you can expect the below, following a chat with one of our Talent Team: Stage 1 - 30 minutes with one of the team Stage 2 - Take-home challenge Stage 3 - 60 minutes technical interview with two team members Stage 4 - 45 minutes final with two data executives
Benefits: 25 days holiday (plus take your public holiday allowance whenever works best for you) An extra day’s holiday for your birthday Annual leave is increased with length of service, and you can choose to buy or sell up to five extra days off 16 hours paid volunteering time a year Salary sacrifice, company-enhanced pension scheme Life insurance at 4x your salary & group income protection Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton Generous family-friendly policies Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing