Staff Data Engineer

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

📋 Description

• Define the architecture and strategy for data platforms encompassing pipelines, warehouses, and data lakes.

• Construct and enhance scalable batch and real-time data processing pipelines.

• Establish and uphold data governance, quality standards, and compliance frameworks.

• Develop monitoring, logging, and alerting systems for data pipelines and related services.

• Contribute to Continuous Integration and Continuous Deployment (CI/CD) workflows for data deployments and automation.

• Propel the modernization of the data platform to enhance performance, cost-effectiveness, and scalability.

• Utilize AI tools such as Claude and Cursor to augment delivery quality and efficiency.

• Design and execute data contracts and event flows in collaboration with backend, platform, and engineering teams.

• Oversee data pipelines for production AI/ML systems, which include embeddings, vector stores, RAG preparation, feature stores, and training/inference workflows.

• Integrate data services with APIs, middleware, and third-party systems.

• Collaborate with leadership to shape data strategy.

• Work alongside engineering, analytics, AI, and product teams.

• Champion data quality, governance, and best practices for the platform.

• Set data engineering standards for the team.

• Mentor junior and mid-level engineers.

• Make critical architectural decisions and manage long-term trade-offs.

⛳️ Requirements

• Over 7 years of professional experience in data engineering, including leading intricate data platform projects.

• Strong background in system architecture with expertise in distributed data systems.

• Advanced proficiency in Python, Scala, and SQL.

• In-depth knowledge of cloud-native data platforms and enterprise data warehousing.

• Extensive experience in orchestrating and processing data pipelines.

• Strong familiarity with streaming platforms and real-time data processing, including Kafka, Kinesis, or Pub/Sub.

• Significant experience in data modeling and transformation.

• Robust knowledge of data quality, governance, and compliance frameworks.

• Proficient in container orchestration and CI/CD practices for data systems.

• Demonstrated experience in building data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows.

• Proven leadership and technical mentorship capabilities.

• Excellent communication skills with stakeholders.

• Proven day-to-day usage and expert knowledge of AI-enhanced coding tools such as Claude and Cursor.

• Strong problem-solving abilities and sound judgment in navigating ambiguous technical and business challenges.

• Experience with data mesh or data fabric concepts, lakehouse architectures, or governance framework implementation is advantageous.

• Experience in handling and modeling healthcare data is a plus.

• AWS certifications, such as Certified Data Engineer – Associate, are highly preferred.

• A successful background check may be necessary.

🏝️ Benefits

• Equal employment opportunities irrespective of protected characteristics.

• Employment offers may include a background check in accordance with local laws.

• Current employer will not be contacted without prior consent.