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