Data Engineer
Zafin is an AI platform company helping regulated institutions modernize how critical work is designed, governed, and delivered. Our technology enables organizations to move faster while maintaining the governance, accountability, and control required in highly regulated environments. Our portfolio includes Zafin AIOS, an agent orchestration platform for governed AI work; the Zafin Banking Platform, which helps banks modernize product, pricing, offers, billing, loyalty, and relationship management; and Zafin IO, an integration platform that connects data, systems, and workflows across complex enterprise environments. Headquartered in Toronto, Canada, Zafin partners with leading financial institutions across North America, Europe, the Middle East, Africa, and Asia-Pacific. As AI transforms the future of financial services, we're building the platforms that help regulated organizations adopt AI responsibly and at scale.What’s the Opportunity? We are seeking a highly skilled Data Engineer II to design, build, and scale robust data platforms that power analytics and product use cases. This role requires strong ownership in developing data pipelines, optimizing infrastructure, and ensuring high standards of data quality, governance, and performance. The ideal candidate brings deep hands-on experience with modern data technologies and thrives in a fast-paced, product-driven environment. What Will You Do? Data Pipeline Development Design, build, and maintain scalable data pipelines for ingesting, transforming, and loading data across batch and real-time (streaming) systems. Integrate data from diverse sources while ensuring reliability, scalability, and efficiency. Data Modeling Design and implement optimized data models, warehouse schemas, and tables for analytics and reporting. Apply best practices in data architecture to support scalable data consumption. Platform & Infrastructure Management Manage and optimize data platforms and infrastructure including Spark, Snowflake, Kafka, Airflow, and Kubernetes. Ensure high availability, scalability, and fault tolerance of data systems. Data Quality & Observability Implement data validation frameworks, automated testing, and monitoring systems. Establish alerting mechanisms to ensure data freshness, accuracy, and completeness. Governance & Security Enforce data governance standards including access controls, data lineage, and compliance. Ensure secure handling of sensitive data (PII) aligned with regulatory requirements. Performance & Cost Optimization Optimize queries, partitioning strategies, file formats, and compute resources. Continuously improve system performance while managing infrastructure costs. Tooling & Automation Develop and maintain CI/CD pipelines for data workflows. Build internal t...