Top Analytics Jobs in Calgary

The Director of Research for Power Markets will oversee the QA/QC process for long-term price forecasts and act as an advisor to leadership, ensuring rigorous review and internal expertise engagement throughout the forecasting cycle.

Lead a developer productivity engineering team to improve the software development lifecycle through metrics, observability, data pipelines, and AI-enabled tools. Own roadmap, mentor engineers, partner with cross-functional leaders, and deliver measurable improvements in adoption, reliability, and developer experience.

Lead product strategy and roadmap for Motive's Telematics data platform. Partner with engineering and AI teams to build API-first products, enterprise integrations, and reliable data services. Drive platform readiness for strategic initiatives, mentor product managers, and align stakeholders across product, engineering, and GTM teams.

Lead and grow a team of 2-3 PMs owning agent tooling and workflows. Define vision and roadmap for agent experience, drive AI-first automation, partner with Operations and cross-functional teams, deliver scalable systems, and measure impact through analytics and experimentation.

Lead and execute the national claims strategy, act as a claims subject-matter expert and liaison across business areas, drive data-informed decision-making, process improvements, and change initiatives. Build business cases, guide senior leadership, identify trends and legal/industry issues, facilitate workshops, and implement processes to enhance client experience, profitability, and staff engagement.

Design, scale, and operate revenue enablement programs for leaders and frontline sellers focused on leader enablement, sales methodology, and new-hire onboarding. Define strategy, operating model, success metrics, and governance. Partner with Sales, Instructional Design, and Analytics to drive adoption and measurable behavior change through blended learning, manager reinforcement, and in-workflow enablement. Track and iterate on program effectiveness to improve manager adoption, methodology adoption, and field productivity.

Lead product strategy for consumer credit, underwriting, merchant pricing, and loan economics. Define features, specs, and metrics; partner with engineering, analytics, design, commercial, legal, and capital to launch and scale products across channels and geographies.

The Technical Success Consultant delivers services ensuring customer success with AVEVA solutions through workshops, coaching, and strategic guidance while promoting adoption and value realization.

Lead pricing analytics for international market expansion: define pricing strategy, structure platform deals, perform economic analyses, run experiments, monitor and iterate pricing and offerings, and partner with cross-functional teams (Product, Credit, Finance, Engineering, Strategic Partnerships).

The Principal Product Manager will define product vision, roadmap, and strategy, ensuring operational excellence while delivering exceptional customer experience and measurable outcomes through cross-functional collaboration.

Partner with prospective and existing customers to lead technical discovery, design integrations and proofs of concept, run tailored demos, troubleshoot implementation issues, and translate customer feedback into product requirements while collaborating closely with sales, product, engineering, and customer success.

Lead a Value Realization Services organization to drive adoption, optimization, and measurable ROI of NICE CX solutions (quality, interaction/speech/text analytics, AI). Manage consulting delivery, operations, revenue, margins, KPIs, and cross-functional alignment while advising senior customer executives and ensuring customer transformation and long-term value.

Own and execute the product vision, roadmap, and delivery for core asset management and tracking software. Lead discovery, define requirements, prioritize backlog, collaborate with engineering/UX, engage customers, measure product metrics, and drive usability, reliability, and scalability improvements. Support launches and adoption with Product Marketing and Customer Success.

Lead technical architecture and roadmap for analytics engineering, build and govern semantic/metrics layers, optimize dbt and Snowflake performance, mentor engineers, partner with Data Science and Data Engineering to deliver AI-ready data foundations and ensure data quality and governance.

Design, build, and maintain dimensional data models, semantic layer, and production data transformation pipelines (dbt/Snowflake). Partner with Data Engineering, Data Science, BI, and Product to deliver governed, AI-ready data products, monitor data quality, enable ML features, and coach junior engineers to uphold code and governance standards.

Senior capital markets product manager/analyst with 15+ years as a Business Analyst. Conduct deep analysis of processes, systems, and workflows; gather and document requirements; analyze trading data, market trends and regulatory changes; use SQL/analytics; familiarity with trading platforms and order management systems is a plus.

Lead and grow a Support Engineering team that resolves complex product issues, integrations, and data workflows. Define escalation and triage practices, build scalable diagnostics and internal tools, collaborate closely with Engineering and Product, mentor engineers on debugging, logs, and database querying, and create repeatable processes to improve customer outcomes and support efficiency.

Lead end-to-end implementations for mid-market and smaller enterprise customers, managing ~15 concurrent 4–8 week SaaS onboarding projects. Develop and execute implementation plans, align stakeholders, configure multi-module systems, drive change management, advise on best practices, and collaborate across CS, Sales, Product, Engineering, and Ops to ensure rapid time-to-value and strong customer outcomes.

Hands-on director-level product designer for enterprise SaaS who owns the design system, user psychology, dashboards, data visualizations, and habit-forming product mechanics. Designs workflows to drive adoption, retention, referrals, and expansion while partnering with Product, Engineering, Sales, and Customer Success. Prototypes, tests, and refines UX based on analytics and A/B experiments to align design with revenue metrics.

Senior pre-sales engineer partnering with sales and channel partners to run technical demos, lead POCs, design solutions, and close large deals. Present to executives and technical audiences, build cloud ML/generative AI solutions, and advise on data architecture and Snowflake positioning.

Lead and mature Solutions & Technical Implementation for Shopify clients: own technical discovery, solution architecture governance, scoping, QA, launch readiness, integrations, analytics/SEO considerations, client-facing technical guidance, and cross-functional coordination across Engineering, PM, SEO, and Analytics.

Drive full lifecycle technical recruiting in Canada: source, screen, and hire technical talent; build sourcing strategies and candidate pipelines; partner with hiring managers; evaluate technical and behavioral fit; manage ATS data and metrics; improve recruiting processes and candidate experience.

Lead PPC and SEO strategy and performance for multiple clients. Own audits, roadmaps, reporting, QA, and team oversight across paid and organic channels. Support sales, standardize playbooks, and build scalable marketing frameworks and dashboards.

Own end-to-end enterprise accounts across Western Canada (Energy, Mining, Utilities). Drive high-velocity customer engagement, pipeline generation, POC-to-production acceleration, account expansion, and accurate Salesforce CRM forecasting while managing complex, multi-stakeholder sales cycles.

Lead design and implementation of Affirm's Lakehouse Platform (Iceberg, Spark, Snowflake). Define technical strategy, enable secure governed access, improve analytics engineering practices, optimize performance and cost, operate at scale, mentor engineers, and collaborate cross-functionally to deliver reliable, discoverable, and cost-efficient analytical data infrastructure.