Senior Backend / Data Platform Engineer – Customer Data
AI in this role
Key Responsibilities
1. Platform Development & Architecture
- Design and implement backend services supporting MADP capabilities
- Contribute to an event-driven architecture (event sourcing, CQRS, messaging)
- Build and evolve platform-level components (not just feature-specific code)
- Ensure solutions are reusable, scalable, and aligned with platform principles
2. API & Integration Design
- Design and implement robust, versioned APIs for data access and integration
- Ensure backward/forward compatibility and stability of API contracts
- Integrate with upstream and downstream systems (e.g. OnePAM ecosystem)
3. Data Modelling & Lifecycle Management
- Contribute to domain-driven data modelling
- Manage schema evolution, ensuring minimal impact on consumers
- Ensure alignment with data governance and data quality rules
- Understand and handle data lifecycle complexity (creation, update, deletion, versioning)
4. Platform Engineering & CI/CD
- Contribute to CI/CD pipelines, branching strategies, and promotion flows
- Support the separation between:
- Platform lifecycle
- Tenant/domain lifecycle
- Improve automation, deployment standards, and engineering practices
5. Operability & Reliability
- Ensure solutions are production-ready and observable
- Contribute to:
- Monitoring & observability
- Incident resolution
- Performance optimization
- Support a high availability, multi-tenant platform
6. Collaboration & Knowledge Sharing
- Work closely with:
- Architects, Data Stewards, and Product Owners
- Operations and Security teams
- Actively document, explain, and share knowledge
- Contribute to a transparent and maintainable platform (no “black box” systems)
Required Skills & Experience
Core Technical Skills
- Strong experience in backend development (Java / Spring Boot or similar)
- Proven experience with event-driven systems (Kafka or equivalent)
- Solid understanding of:
- Event sourcing and CQRS patterns
- Distributed systems design
- Strong experience in API design and integration patterns
Data & Platform Expertise
- Experience with:
- Data modelling (schema design, evolution)
- Handling data lifecycle and versioning
- Familiarity with data governance and access control concepts
- Experience building or contributing to platforms (not just applications)
DevOps & Engineering Practices
- Knowledge of:
- CI/CD pipelines
- Git branching strategies
- Deployment and release management
- Familiarity with cloud and distributed infrastructure
How we score this
Senior Backend / Data Platform Engineer – Customer Data at ING scores 27 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.
AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.
- AI Level 480 to 100
- AI Level 360 to 79
- AI Level 240 to 59
- AI Level 10 to 39
Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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