Platform Engineer
We are looking for a senior engineer to join our core platform team. You will be responsible for developing and maintaining two sophisticated analytical platforms:
- Self-Service Analytics Platform: An internal system that enables data engineers to autonomously create and manage their own workspaces, Databricks resources (clusters, catalogs, schemas), and candidate trusted datasets with granular access control.
- Secure Collaboration Platform: A fully isolated environment designed for secure collaboration with external partners, requiring strict network isolation and high-level security standards.
Your role is to build the "engine" that automates cloud infrastructure. We use Python for backend logic and CDKTF to define our cloud footprint, ensuring a seamless, code-driven experience for our users.
Requirements
- Senior Python level: Extensive experience in Python, specifically for cloud-native applications or serverless architectures
- IaC Mastery: Strong experience with Terraform. Previous experience with CDK patterns (writing infrastructure using programming languages) is a major advantage
- Azure Ecosystem: Deep knowledge of Azure cloud services, networking, security and identity management
- Data Platform Familiarity: Understanding of modern data platform architectures (e.g., Databricks, Snowflake, or similar)
- DevOps Mindset: Professional experience with Git, CI/CD pipelines (Azure DevOps preferred), and automated testing
Nice to have
- Security-First Mindset: Experience building and maintaining isolated/air-gapped environments
- API & Frontend Integration: Experience building APIs for low-code frontends or complex web applications
- Enterprise Tooling: Familiarity with Incident Management tools (e.g., ServiceNow)
Responsibilities
- Platform Backend Development: Develop and scale Python-based microservices using Azure Function Apps (HTTP/Event triggers)
- Infrastructure as Code (IaC): Automate the entire lifecycle of cloud resources (clusters, databases, networking) using CDKTF (Cloud Development Kit for Terraform) in Python
- Data Governance & Security: Implement fine-grained access control for datasets (row, column, and table-level security) within the platform
- System Integration: Design and maintain robust APIs that asynchronously integrate with external frontend tools (Mendix-based)
- Operational Excellence: Maintain platform stability, troubleshoot complex backend issues, and provide Tier-3 technical support for advanced users
- Agile Collaboration: Actively participate in all Scrum ceremonies (2-week sprints) and manage CI/CD pipelines via Azure DevOps
Platform Engineer
What will be your next steps?
Quick non-technical conversation
Our initial conversation is a brief, non-technical discussion to understand your background and career aspirations. We're keen to learn about your communication style and how you approach teamwork and decision-making.
60 to 90 minutes technical interview
This in-depth technical assessment, lasting 60 to 90 minutes, is designed to evaluate your specific skills and expertise. We will present you with challenges relevant to our client's requirements.
Client interview
In this stage, you will meet directly with the client for a final technical discussion. This interview will be similar in format to our internal technical assessment, allowing the client to see firsthand how your expertise aligns with their specific project needs and team.
Offer
Congratulations on successfully completing our rigorous evaluation process. We are pleased to extend an offer and recommend you to our clients.