Senior Engineer, Data Enablement, Data Platforms
CPP Investments View all jobs
- Toronto, ON
- Permanent
- Full-time
- Build and support Data Enablement services and platform components to improve data discovery, access, and self-service experiences
- Collaborate with users and stakeholders to gather feedback and refine features to ensure solutions are practical and adopted
- Develop solutions with performance, scalability, resiliency, and security in mind, following DevSecOps and operational standards
- Contribute to solution design and documentation (e.g., LLD, interface specifications) and support governance processes (ARB, Information Security)
- Partner with Cloud Foundation and Data Foundation teams to integrate with shared services, entitlements, and platform standards
- Build and maintain backend services (serverless and containerized where appropriate) that support enterprise data platforms and portals
- Implement and maintain APIs, including contracts, versioning, and data validation
- Contribute to workflow automation capabilities within Data Enablement solutions under enterprise controls
- 5+ years of software engineering experience delivering production-grade services using Python
- Strong experience with AWS cloud platform, including networking and secure access patterns
- Solid understanding of identity and access management (IAM, authentication/authorization patterns)
- Experience building backend services and APIs (REST/GraphQL, event-driven architectures, resiliency patterns)
- Hands-on experience with Infrastructure-as-Code and DevSecOps practices (e.g., Terraform, CI/CD, security controls)
- Experience with observability and reliability practices (monitoring, alerting, incident response)
- Strong API design experience (OpenAPI/Swagger, versioning, backward compatibility)
- Experience working with structured data formats and schema processing (e.g., JSON)
- Working knowledge of authentication and authorization patterns (e.g., Cognito, IAM)
- Experience with agentic or orchestration frameworks (e.g., AWS Bedrock, LangChain, LlamaIndex)
- Understanding of retrieval approaches such as RAG and GraphRAG
- Experience with vector search technologies (e.g., OpenSearch, Pinecone, Weaviate)
- Familiarity with containerization and platform operations (e.g., Docker, Kubernetes/EKS)
- Experience integrating with enterprise data platforms, catalogs, or governed access patterns
- AWS Data & Analytics certification; ML-related certification is a plus