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
Qualifications 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




Assets 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)
Skills required for success Technical Mastery: 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
Cloud & Orchestration Expertise: 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
Pipeline Reliability: 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
Analytics & Visualization: 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
Communication & Collaboration:



Clear communication skills with proven ability to translate complex ETL/AI technical concepts into accessible insights for diverse non-technical team members and collaborators
Problem Solving & Time Management: 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 ( https://bit.ly/4brRrXm)
Embracing a culture of equity, diversity, reconciliation and inclusion
Conditions of Employment Satisfactory completion of relevant background checks prior to commencement
Work Environment This role primarily operates in a standard, modern office setting with options for hybrid working arrangements in accordance with City of Edmonton policies
Physical demands are minimal and typical of a computer-focused administrative position
The weekly hours of work for this position are currently under review and may change at a future time. Any changes will be made in accordance with the City of Edmonton/Civic Service Union 52 collective agreement, and the incumbent will be notified in advance
The City of Edmonton values applicants with a diverse range of skills, experiences and competencies, and encourages you to apply. We strive to provide reasonable access and accommodations throughout the recruitment process. To request an accommodation, please contact [email protected]
Learn more about our perks https://bit.ly/COEbenefits
Hours of Work: 40 hours per week
Salary Range: $48.774 - $61.628 (Hourly) $101,840.110 - $128,679.260 (Annually)
Edmonton rests in the heart of Treaty Six territory in Alberta and the homelands of the Métis Nation.

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📌 Cloud Data Analyst (Methods Analyst II) (Alberta)
🏢 City of Edmonton
📍 Alberta