Cloud Data Analyst (Methods Analyst II)
About The Position
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!
Requirements
- University Degree in Computer Science, Software Engineering, Management Information Systems, Data Science/Analytics, Applied Statistics, Operations Research, or a directly related technical field
- Minimum of four (4) years of directly related hands-on experience in programmatic data engineering, cloud data architecture, and enterprise ETL/ELT pipeline development
- Deep proficiency in programmatic data manipulation using Python and advanced analytical SQL. Highly capable of writing complex time-series logic utilizing Common Table Expression (CTEs) and Window Functions
- Demonstrated ability to manage cloud data warehouses and implement structural optimizations like table partitioning and clustering in Google BigQuery.
- Proven experience orchestrating complex production pipelines using Apache Airflow or dbt / Dataform, while adhering to software delivery best practices including Git and CI/CD
- Proven track record of designing highly scalable, idempotent ETL/ELT pipelines that can process massive daily data volumes and safely recover from automated failures without duplicating records
- Strong proficiency in applied statistics, enterprise BI tools (Tableau, Looker, PowerBI), and advanced data analytics (descriptive, diagnostic, and predictive). Demonstrated ability to go beyond basic reporting by transforming massive pipeline outputs into strategic, actionable insights that solve operational transit problems
- Clear communication skills with proven ability to translate complex ETL/AI technical concepts into accessible insights for diverse non-technical team members and collaborators
- Exceptional ability to independently navigate and process massive, high-velocity data streams under tight deadlines while balancing short-term operational demands with long-term architecture goals
- Strict adherence to fiscal responsibility, demonstrating the ability to proactively balance scalable data architecture with rigid cloud compute budgets to prevent cost overruns
- Alignment to our Cultural Commitments and Leadership Competencies
- Embracing a culture of equity, diversity, reconciliation and inclusion
Nice To Haves
- Google Cloud Professional Data Engineer or Google Cloud Professional Machine Learning Engineer certifications
- Formal credentials or demonstrated experience in modern Generative AI, Large Language Models (LLMs), or agentic AI frameworks
- Experience or training in modern data orchestration tools (e.g., Apache Airflow, dbt)
Responsibilities
- 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
- Continuously evaluate data compute environments using advanced SQL, table partitioning, and clustering techniques to ensure fiscal responsibility and performance efficiency
- 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
- 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
- Facilitate the Annual Operator Vacation Sign-Up process for nearly 2,000 transit operators, balancing operational needs with collective agreement parameters
- 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
- Actively partner with analysts across Edmonton Transit Service (ETS) to ensure enterprise pipelines align with diverse operational workflows and municipal requirements
Benefits
- hybrid working arrangements in accordance with City of Edmonton policies
- Learn more about our benefits https://bit.ly/COEbenefits
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
