Lead Analytics Solutions Developer

Role: Lead Analytics Solutions Developer  Status: Full Time  Reports to: Senior Manager, Data Strategy & Analytics  Location: MarkhamCompensation: $102,912 - $149,738Please note that the compensation range listed includes base salary and potential incentive pay. Incentives such as bonuses are not guaranteed and depend on individual performance and company results. Actual compensation within the range will be determined based on skills, experience, and qualifications.   Summary  The Lead Analytics Solutions Developer is the senior technical authority for how Enercare’s business data is modelled, defined and delivered for analysis. You will design the data structures and calculation logic that our field operations, finance, supply chain, marketing and customer teams rely on to run the business — and you will be accountable for making sure those numbers are consistent, explainable and trusted.The problems you will take on are real and current. Demand for answers is growing faster than any team can build individual reports to satisfy, so the opportunity is to define business logic once, govern it well, and make it reusable everywhere it is needed. That same foundation is what makes AI-assisted analytics work: a well-designed semantic and ontology layer — governed metric definitions, clear relationships between business entities, and the context that tools such as Model Context Protocol (MCP) servers and conversational agents depend on — is what allows natural-language questions to return grounded, accurate answers rather than confident-sounding but incorrect ones. Your work directly addresses these: working closely with architects in setting the technical strategy, designing reusable, well-governed data products and establishing the definitions that let the organization operate from one version of the truth.This role requires more than technical depth. You will be making judgement calls on where logic should live, when to build for reuse versus solve for speed, and which of two competing definitions the enterprise should adopt — often with stakeholders who each have a legitimate view. Equally important is a genuine understanding of how the business runs: the journeys a job, a customer or an asset moves through end-to-end, so that the solutions you design surface the analysis and the “so what” straight out of the box, rather than leaving someone to assemble the story afterwards. Strong technical craft gives you the credibility; sound judgement, business fluency and the ability to lead without authority are what make the decisions stick. You will set the technical direction for the Analytics Solutions track, mentor the developers within it, and represent the team’s work in forums.Responsibilities  Own the design of Enercare’s core analytical data models — the structures, dimensions and calculation logic that business reporting and analysis are built on.  Own the enterprise metric definitions: what each measure means, how it is calculated, where it applies and when it should not be used.  Build reusable, certified data products so business logic is defined once and consumed consistently, rather than rebuilt inside individual reports.  Design for a harmonized, enterprise-wide view of the business rather than a collection of regionally segregated ones. Today our operations are represented separately — West, East and Ontario each sit in their own estate — and a strong candidate will design a target state that brings them onto common, conformed structures in a way that is scalable, robust and able to absorb future regions or acquisitions.  Design the semantic and ontology layer — entities, relationships and business vocabulary — so that both people and AI tools can interpret our data correctly and return trustworthy answers.  Partner with operations, finance and commercial teams to understand the decisions being made, then design solutions that genuinely support them.  Model the end-to-end journeys that matter to the business — how a job, customer or asset progresses through its lifecycle — so analysis and insight are available by design rather than assembled after the fact.  Resolve data discrepancies and reconciliation issues at root and translate the explanation into terms a business leader can act on.  Ensure what we build is reliable, repeatable and safe to change, so the business can depend on it without having to re-verify the numbers — setting the development disciplines that make that true: version control, code review, testing and documentation expectations.  Set and uphold release discipline for the analytics track, working within the CI/CD capability provided and supported by the Data Engineering team, and holding our own delivery to those standards.  Own lineage and metadata practice so every metric is traceable from dashboard back to source, and any number can be explained on demand.  Mentor Analytics Solutions Developers and Senior Analytics Solutions Developers; lead design reviews and set technical direction for the track.  Act as the escalation point for complex modelling decisions and contentious data investigations.  Work with Finance, Operations and Commercial teams to reconcile competing metric definitions and drive to a single agreed standard.  Build credibility with senior stakeholders so that technical recommendations are trusted and adopted.  Qualifications  8+ years in analytics development, BI development or data warehousing, with demonstrated ownership of a business domain end-to-end. Data Modelling: Expert-level dimensional and analytical modelling; able to set standards, not just follow them. SQL: Advanced T-SQL including window functions, performance tuning and complex business logic. Power BI: Deep DAX and semantic model design, including row/column-level security and large-model performance optimization. Cloud Data Platform: Hands-on delivery on a modern cloud data platform, with a clear view of how responsibilities are divided across a layered architecture. Definitional Judgement: Proven experience defining metric standards and driving alignment where functions disagree on the numbers. Business Fluency: Able to learn how an operation actually runs and reflect those journeys and processes in the solutions you design. Leadership: Track record mentoring developers and leading technical decisions without direct reporting authority. Communication: Able to explain technical trade-offs and data issues credibly to non-technical senior stakeholders. dbt or an equivalent transformation and metric-layer framework, including semantic layer definitions and CI/CD for data assets. Experience designing ontologies, knowledge graphs or business glossaries that make enterprise data machine-interpretable. Exposure to enabling AI-assisted or natural-language analytics — for example Model Context Protocol (MCP) servers, retrieval grounding, or agent tooling over governed data — with an understanding of how data design reduces hallucination. Experience consolidating a fragmented reporting estate into a governed, reusable set of data products. Microsoft Fabric or equivalent cloud native platforms, Direct Lake semantic models, or lakehouse architecture experience. Field-service, utilities, home-services or workforce/capacity analytics domain experience.