Senior Data Engineer

Have you heard of BlueCat? We’re one of those hidden gems that’s been disrupting the market as a key player in the rapidly growing space of Intelligent Network Operations. Organizations require a new model of network operations that links foundational core services with a deep, predictive understanding of network health and performance to improve change readiness. BlueCat’s Intelligent NetOps is a first-to-market combination of systems of understanding and change. BlueCat enables teams to enhance agility and mitigate risks from high rates of change with a unified management lifecycle, from provisioning to proactive troubleshooting and remediation. At BlueCat, we take immense pride in our award-winning culture, an integral part of our identity. We are proud recipients of several prestigious accolades, including the "Great Place to Work" certification. By becoming a part of our team, you not only join a company at the forefront of technology but also become an integral member of Canada's top workplaces in various categories, including Technology, Today's Youth and Women, and Mental Health and Inclusion. The BlueCat Cloud Platform team is dedicated to powering all BlueCat SaaS products. Our mission is to deliver these products on a reliable, fast, globally distributed, and cost-effective enterprise-grade cloud infrastructure. A key aspect of this mission is our scalable data service, which supports the growth of BlueCat's data-driven products. We are seeking a highly skilled Senior Data Engineer with strong ownership, communication, and collaboration abilities to join our team. In this role, you will help us automate a robust and scalable data service used by numerous teams across the company. Key Responsibilities: • Design, build, and operate a large-scale data lake • Build and maintain data pipelines and data services • Implement data processing and analytics jobs • Work closely with Application and Platform teams on data requirements • Contribute to architecture, scalability, and performance decisions • Ensure data quality, reliability, and observability • Optimize system performance, scalability, and reliability • Ensure data protection across the data lifecycle Core Requirements: • Strong proficiency in Python and SQL • Experience with distributed data processing (Spark or Flink) • Hands-on experience with modern data lakehouse architectures • Solid understanding of data modeling and warehousing concepts • Experience building and maintaining reliable data pipelines • Experience with AWS (or other cloud platforms) • CI/CD experience (GitLab preferred, GitHub or Bitbucket) • Infrastructure as Code (Terraform or similar) • Kubernetes (K8s) • Understanding of OLAP vs OLTP systems • Dimensional modeling (Kimball, star schema, surrogate keys, Slowly Changing Dimensions) Nice to Have: • Experience with data observability, monitoring, and data quality practices • Monitoring tools: CloudWatch, Prometheus, Grafana • Apache Iceberg • ClickHouse • Orchestration tools: Dagster or Apache Airflow