Analytics Engineer
Role Overview
An early-career Analytics Engineer joins Customer Operations and reports to the Senior Director, Customer Experience.
The role turns data from Advanced Metering Infrastructure deployments into actionable insights for utilities and internal teams.
The work spans utility operations, data analytics, AI, and customer outcomes.
Key Skills for This Role
Full Job Posting
About Tantalus
Tantalus provides smart-grid devices, communications networks, data management, enterprise applications, and analytics for utilities.
The company operates in the United States and Canada and has offices including Burnaby, British Columbia.
The Opportunity
An early-career Analytics Engineer joins Customer Operations and reports to the Senior Director, Customer Experience.
The role turns data from Advanced Metering Infrastructure deployments into actionable insights for utilities and internal teams.
The work spans utility operations, data analytics, AI, and customer outcomes.
Role Location
- This is a hybrid role based in a Tantalus office in Burnaby, British Columbia; Chattanooga, Tennessee; or Raleigh, North Carolina.
Responsibilities
- Build automated reports, dashboards, and analytical workflows using AMI, outage, power-quality, and utility operations data.
- Develop trend analysis and benchmarking to demonstrate deployment value, performance improvements, relative cost positions, and operational outcomes.
- Analyze outages, reliability, power quality, device performance, and other metrics to identify trends, risks, and opportunities.
- Enhance analytics models and reporting frameworks; apply AI, machine learning, and automation to improve reporting and insights.
- Support analytics onboarding through data validation, report configuration, and ongoing customer reporting.
- Partner across Customer Operations, implementation, Product, Engineering, Analytics, and NOC teams to build scalable reporting solutions.
- Prepare reports, visualizations, and documentation to support decision-making and continuous improvement.
Education and Experience
- Bachelor’s degree in Computer Science, Data Science, Software Engineering, Statistics, Mathematics, Engineering, or a related field.
- 0–2 years of relevant experience in analytics, data science, software development, AI/ML, business intelligence, or a related technical field.
- Proficiency in Python and experience using SQL to query, manipulate, and analyze data.
- Experience with data analysis, visualization, or machine learning tools for reports, dashboards, or analytical solutions.
- Foundational understanding of statistics, machine learning, data analytics, and data visualization.
- Experience building dashboards, reports, data pipelines, automated workflows, analytical applications, or internal tools.
- Internship, co-op, academic project, or research experience in a related area is considered valuable.
Capabilities and Attributes
- Translate ambiguous business questions into structured analytical approaches and practical outputs; bring strong analytical, problem-solving, and critical-thinking skills.
- Communicate technical findings clearly to technical and non-technical audiences.
- Work independently, manage priorities, collaborate across functions, and adapt to evolving needs.
- Bring curiosity, attention to detail, customer focus, resourcefulness, and interest in AI, analytics, and emerging technologies.
Compensation and Benefits
- The position offers competitive salary plus variable compensation based on performance targets and business objectives.
- Benefits include medical, dental, vision, flexible spending accounts, and paid time off.
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