Cloud Data Analyst (Methods Analyst II)

Are you passionate about leveraging modern cloud data architecture and artificial intelligence to make a tangible impact on public transit? Edmonton Transit Service (ETS) is looking for an innovative and collaborative Cloud Data Analyst to act as the cloud infrastructure expert of our team. In this pivotal role, you will architect and scale end-to-end data pipelines (ETL/ELT) on the Google Cloud Platform, transforming over million rows of complex and raw transit telemetry daily into actionable insights and advanced AI models. Your technical expertise will directly support daily transit operations, optimize workforce scheduling for over 2,000 transit operators, and continuously improve the transit experience across our city. If you are driven by cloud computing efficiency, pipeline reliability, and writing scalable production code, this is your opportunity to build upon our existing enterprise architecture and scale it for the AI era! What will you do? - Build & Scale Data Architecture: Design, maintain, and optimize robust ETL/ELT pipelines in Google Cloud Platform (GCP) and BigQuery to process over a million rows of transit data daily - Optimize Cloud Costs & Performance: Continuously evaluate data compute environments using advanced SQL, table partitioning, and clustering techniques to ensure fiscal responsibility and performance efficiency - Automate Data Quality: Create automated validation framework rules to systematically clean data anomalies such as duplicate bus pings, corrupted data payloads and logical outliers - before data feeds AI agents and downstream applications - Enable Data-Driven Decision Making: Leverage applied statistics and predictive analytics to solve complex transit business problems. Transform the outputs of massive data pipelines into clear, enterprise-grade dashboards (using tools like Tableau or Looker) that empower cross-functional leadership to make strategic, data-informed decisions - Operational Support: Facilitate the Annual Operator Vacation Sign-Up process for nearly 2,000 transit operators, balancing operational needs with collective agreement parameters - Enable AI & Predictive Analytics: Structure and provision clean, reliable enterprise data feeds that serve as the foundational truth. In future phases of the roadmap, build, configure and deploy the AI micro-agents and predictive models that utilize this data - Cross-Functional Collaboration: Actively partner with analysts across Edmonton Transit Service (ETS) to ensure enterprise pipelines align with diverse operational workflows and municipal requirements