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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining high-performance data pipelines and analytics platforms, with a strong focus on AI integration and API design. Proficient in cloud-native infrastructure and containerization, ensuring data quality and reliability in production environments.
Highest-signal resume keywords
Data Pipeline DevelopmentAI IntegrationAPI Design and IntegrationCloud-Native InfrastructureEvent-Streaming Technologies
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonData ModelingPostgreSQLUnit TestingEnd-to-End TestingKafkaDockerKubernetesData QualityProduction SLOs
Soft Skills
CollaborationCommunicationProblem-SolvingProfessional Growth Support
Tools & Technologies
AzureAWSGCPFlinkNATSAI-Assisted Development ToolsIcebergTrino
Industry Keywords
Data FabricReal-Time IngestionStreaming ExperienceBillingFinanceUsage-Based MonetizationProduction-Ready Systems
Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformKafkaKubernetesPostgresPython
About the role
Key responsibilities & impact- Design, build, and evolve CloudBlue’s data and analytics platform
- Build and maintain a high-volume, high-performance data fabric, including real-time ingestion, data pipelines, storage, and analytics
- Own features end to end, from technical design and implementation through testing and production
- Drive AI adoption across the platform and develop AI-powered workflows and capabilities
- Design and integrate APIs connecting data, services, and business workflows across the CloudBlue ecosystem
- Work closely with engineers in small, cross-functional feature teams
- Collaborate with Product Managers and other CloudBlue teams to translate business needs into scalable technical solutions
- Ensure data quality, reliability, observability, and performance across production pipelines
- Partner with the Engineering Manager on professional growth and career development
- Support other tasks or projects as assigned to meet team and business needs
Requirements
What you’ll need- Strong professional software engineering experience, with a solid background in building data-intensive systems
- Extensive experience building data pipelines and data models, including production-scale data workloads
- Hands-on experience with Python
- Strong expertise with event-streaming technologies such as Kafka, NATS, Flink, or similar; streaming experience is essential
- Experience with cloud-native infrastructure such as Azure, AWS, or GCP
- Experience with containerized workloads using Docker and Kubernetes
- Solid understanding of data contracts, data quality, pipeline observability, and production SLOs
- Hands-on experience with AI-assisted development tools and genuine interest in applying AI to engineering problems and development workflows
- Strong experience designing and integrating APIs
- Solid knowledge of PostgreSQL and relational databases
- Experience with unit and end-to-end testing and building reliable, production-ready systems
- Professional working proficiency in English
- Familiarity with billing, finance, or usage-based/metered monetization is a plus
- Exposure to integrating LLMs or AI services, such as RAG, MCP, agent runtimes, Anthropic/OpenAI APIs, or similar technologies, is an advantage
- Experience with modern lakehouse or data federation patterns, such as Iceberg, Trino, or similar technologies, would be beneficial
- Candidates must respond to questions about production real-time streaming pipelines and AI engineering experience
- Willingness to participate in standard candidate verification steps, where permitted by applicable law
- Acknowledgment that employment history and application information may be verified
- The position is anticipated to be performed outside of Ontario
Benefits
Comp & perks- Competitive pay, benchmarked against the markets we hire in
- Room to grow, with real ownership of your work and support for professional development
- Flexibility in how and when you work, within the core hours your team needs
- Access to the AI tools you need to do your work, and the room to experiment with them
- Remote-first work
- Equal-opportunity employer
- Accommodations for people with disabilities at every stage of the hiring process