Senior Data Engineer

Posted Aug 19

This is a fully remote position, open to applicants in Canada.

📋 Description

• Develop and sustain a high-volume, high-performance data fabric, which includes real-time data ingestion, data pipelines, storage, and analytics.

• Take ownership of features from inception to completion, encompassing technical design, implementation, testing, and deployment.

• Propel AI integration throughout the platform and create AI-driven workflows and functionalities.

• Design and connect APIs that link data, services, and business processes within the CloudBlue ecosystem.

• Collaborate closely with engineers in small, cross-functional feature teams.

• Work in conjunction with Product Managers and other CloudBlue teams to convert business requirements into scalable technical solutions.

• Guarantee data quality, reliability, observability, and performance across production pipelines.

• Partner with the Engineering Manager to foster professional growth and career development.

• Assist with additional tasks or projects as needed to fulfill team and business objectives.


⛳️ Requirements

• Significant professional software engineering experience in constructing data-intensive systems.

• Extensive background in building data pipelines and data models, including managing production-scale data workloads.

• Practical experience with Python.

• Deep knowledge of event-streaming technologies such as Kafka, NATS, Flink, or similar; experience in streaming is crucial.

• Familiarity with cloud platforms like Azure, AWS, or GCP.

• Proficiency in Docker and Kubernetes.

• Strong understanding of data contracts, data quality, pipeline observability, and production service level objectives (SLOs).

• Hands-on experience with AI-assisted development tools.

• Significant experience in designing and integrating APIs.

• Solid knowledge of PostgreSQL and relational database systems.

• Experience with unit testing and end-to-end testing, ensuring the development of reliable, production-ready systems.

• Professional working proficiency in English.

• Familiarity with billing, finance, or usage-based/metered monetization is advantageous.

• Exposure to large language models (LLMs) or AI services, such as RAG, MCP, agent runtimes, Anthropic/OpenAI APIs, or similar technologies, is a plus.

• Experience with modern lakehouse or data federation patterns, such as Iceberg, Trino, or comparable technologies, would be beneficial.


🏝️ Benefits

• Opportunities for career advancement and professional development.

• Flexible work arrangements to promote work/life balance.

• Remote work option available.

• Competitive salary.

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