Sr. Analytics Developer - Supply & Trading; S&T

Position: Sr. Analytics Developer - Supply & Trading (S&T)
** A little about Capital Power
** Capital Power (TSX: CPX) is dedicated to
* Powering Change by Changing Power*. This north star guides our ambitions, focus, and actions as we transform our energy system. We're a growth-oriented North American energy company headquartered in Edmonton, Alberta. Our team safely delivers, builds, and creates balanced energy solutions for customers across North America.

Our people are at the core of our journey to deliver reliable, affordable, and lower-carbon power solutions. We provide purpose-driven work in a safe and inclusive environment, and we live by our . With us, your contributions matter – we want you to be empowered to innovate, collaborate, and ultimately drive results. We're here to partner with you so you can learn, grow, and forge a career that's meaningful to you.

Join us in powering North America!
** Your Opportunity
** One Permanent Full Time Position.

The Sr. Analytics Developer supports the Supply & Trading (S&T) function through the expansion, definition, and delivery of analytics that enable effective contractual and trading decision-making. It is a high-touch, business-embedded role that works closely with trading stakeholders to shape analytical outputs within the context of Capital Power’s
** Enterprise Oversight Framework (EOF)** — the company’s proprietary enterprise reporting foundation.

The Sr. Analytics Developer - Supply & Trading (S&T) acts as a
** bridge between business-facing analytics and core data engineering**, translating complex, high-volume transactional trading data into governed, scalable data models and analytical products aligned with enterprise standards.

You will contribute to our team by:
** Key Responsibilities
*** Partner closely with Supply & Trading stakeholders to define analytical requirements, success criteria, and decision-support outputs
* Translate trading and commercial questions into well-designed analytical solutions aligned to EOF principles (UI/UX) and enterprise reporting standards
* Work hands-on with high-volume transactional trading data, including deals, volumes, prices, settlements, and related structures
* Design and develop analytical data models that reflect trading domain logic while conforming to enterprise data and Dev Ops standards
* Build and maintain reliable data transformations and analytical layers, with support from the Data Operations squad
* Ensure data accuracy, reconciliation, and traceability from source trading systems through to analytical and reporting outputs
* Collaborate with data engineers, analytics developers, and Dev Ops leads to ensure solutions are production-ready, maintainable, and scalable
* Contribute to documentation, metric definitions, and lineage to support transparency, governance, and long-term sustainability
** Required Experience & Capabilities
*** 8+ years experience in analytics engineering, data analytics, data engineering, or a senior hybrid role
* Strong SQL and data modeling skills, particularly with high-volume, financially transactional datasets
* Working knowledge of trading, commercial, or market-based data structures (energy, commodities, or similar environments)
* Proven ability to operate in a
** bridge role** — engaging deeply with business stakeholders while delivering technically sound solutions
* Experience working within modern data platforms and cloud environments (e.g., Snowflake, Databricks, Azure)
* Comfort operating within structured delivery models, including Dev Ops-aligned development and release practices
** Ways of Working:
*** High stakeholder engagement and iterative solution definition
* Outcome-focused, with strong emphasis on clarity, accuracy, and decision usefulness
* Collaborative delivery alongside data engineering, data operations, and analytics teams
* Operates effectively in ambiguous problem spaces where requirements evolve through discussion and discovery
*
* Education:

**
* ** Bachelor’s degree
** in a quantitative or technical field such as Computer Science, Engineering, Mathematics, Statistics, Information Systems, or a related discipline.
* ** Master’s degree
** or in Data Science, Engineering, Analytics, Statistics, or a related field…