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Remote, United States
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Tantalus

Analytics Engineer

Raleigh, NC, United States

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Job details

Experience: 0–2 years of relevant experience in analytics, data science, software development, AI/ML, business intelligence, or a related technical field.
Posting language: English
Posted: Nov 4, 2026

Original job description

About Tantalus Systems (TSX: GRID)

Tantalus is a technology company dedicated to helping utilities modernize their distribution grids by harnessing the power of data across all their devices and systems deployed throughout the entire distribution grid – from the substation to the EV charger located behind the meter. We offer smart grid solutions across multiple levels: intelligent connected devices, communications networks, data management, enterprise applications and analytics. Learn more at http://www.tantalus.com/.

Come join us if you’re interested in being part of an entrepreneurial team, solving complex technical problems and delivering innovative solutions that will directly impact the electrification of everything and the decarbonization of our society.

We have operations throughout the United States and Canada with offices in Burnaby (British Columbia, Canada), Raleigh (North Carolina, USA), and Norwalk (Connecticut, USA).

This position offers a competitive salary plus variable compensation based on performance targets and business objectives. Tantalus also offers generous benefits, including medical, dental and vision plans, healthcare and dependent care flexible spending accounts and paid time off.

The Opportunity

Tantalus is seeking an early-career Analytics Engineer to join our Customer Operations team, reporting to the Senior Director, Customer Experience.

In this role, you will help turn data from Tantalus Advanced Metering Infrastructure (AMI) deployments into clear, actionable insights for utilities and internal teams. You will build reporting tools, automated analyses, dashboards, benchmarks, and data-driven workflows that demonstrate how Tantalus solutions are improving outage response, power quality, system reliability, and operational performance.

This is an opportunity to work at the intersection of utility operations, data analytics, AI, and customer outcomes. You will help customers understand the measurable value of their Tantalus deployments while supporting internal teams with the insights needed to improve onboarding, service delivery, network operations, and future analytics offerings.

Role Location

This is a hybrid role based in one of Tantalus' offices in Burnaby, BC; Chattanooga, TN; or Raleigh, NC.

Specifically, the Analytics Engineer will:

Build and enhance automated reporting tools, dashboards, and analytical workflows using AMI, outage, power quality, and utility operational data.
Develop reporting and trend-analysis capabilities that help customers quantify the operational value and performance improvements delivered through their Tantalus deployments
Analyze outage performance, reliability, power quality, device performance, and other operational metrics to identify meaningful trends, risks, and improvement opportunities.
Support the development of benchmarking models that compare performance across customer deployments and help utilities understand their relative cost position and operational outcomes.
Enhance existing analytics models, reporting frameworks, and internal analytics initiatives.
Apply AI, machine learning, and automation techniques to improve reporting accuracy, scalability, and insight generation.
Work with Customer Operations and implementation teams to support customer onboarding to analytics offerings, including data validation, report configuration, and ongoing reporting needs.
Partner with Product, Engineering, Analytics, and NOC teams to identify data requirements and deliver practical, scalable reporting solutions.
Help develop analytics and reporting capabilities that support the growth and ongoing operation of Tantalus’s Network Operations Center.
Prepare analytical reports, visualizations, and documentation that support data-driven decision making and continuous improvement.

What you Bring:

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, including experience using Python for data analysis, automation, reporting, or machine learning applications.
Experience querying, manipulating, and analyzing data using SQL.
Experience using data analysis, data visualization, or machine learning tools to develop reports, dashboards, or analytical solutions.
Internship, co-op, academic project, or research experience involving data analytics, machine learning, software development, or reporting solutions is considered valuable.
Foundational understanding of statistics, machine learning, data analytics, and data visualization principles.
Experience building dashboards, reports, data pipelines, automated workflows, analytical applications, or internal tools.
Ability to translate ambiguous business questions into structured analytical approaches and practical outputs.
Strong analytical, problem-solving, and critical-thinking skills.
Strong verbal and written communication skills, with the ability to explain technical findings clearly to technical and non-technical audiences.
Ability to work independently, manage priorities, and collaborate effectively in a hybrid, cross-functional environment.

Personal Attributes Required

Curious and eager to learn, with a strong interest in AI, analytics, and emerging technologies.
Self-motivated and able to work independently while managing competing priorities in a hybrid work environment.
Strong problem-solving skills with the ability to think critically and approach challenges with creativity and resourcefulness.
Detail-oriented with a commitment to delivering accurate, high-quality work.
Collaborative team player who enjoys working across departments and building relationships with both technical and non-technical stakeholders.
Customer-focused mindset with a desire to understand customer needs and translate data into meaningful business outcomes.
Effective communicator with the ability to explain complex information in a clear and concise manner.
Adaptable and comfortable working in a fast-paced environment where priorities and business needs may evolve.

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