Top Analytics Jobs in Calgary

Leads Sales Development across North America and the UK, owning top-of-funnel pipeline performance, team integration, reporting, targeting, conversion, and revenue contribution. Builds scalable inbound and outbound motions, expands upmarket coverage, develops managers and representatives, and partners with Marketing, Sales, Finance, Risk, Compliance, Product, and Operations. Uses analytics, automation, and AI to improve prospecting and productivity while establishing rigorous planning, coaching, qualification, and performance standards.

Build and scale AI-first marketing enablement systems, workflows, integrations, playbooks, learning resources, and measurement dashboards. Own department-wide initiatives including AI transformation, onboarding, and acquisition integration. Evaluate and deploy tools with IT and Legal, establish governance and access controls, identify capability gaps, drive adoption, and measure outcomes such as productivity, engagement, and process effectiveness.

Manage and grow strategic end-customer accounts across Canada. Develop multiyear account plans, build executive and technical relationships, identify expansion opportunities, lead proposals and account reviews, coordinate cross-functional teams and channel partners, manage forecasts in Salesforce, and support demonstrations, pilots, escalations, retention, and sustainable revenue growth. The role is based in Vancouver or Calgary and requires travel up to 50% of the time.

Leads Marketing and Consumer Privacy Engineering teams, developing engineers and establishing a shared operating model. Translates business and product priorities into engineering plans across logged-out web, experimentation, marketing integrations, attribution, measurement, consent, privacy experiences, and consumer data collection. Partners with Product, Marketing, Privacy, Legal, and Engineering stakeholders to deliver reliable, scalable, privacy-aware systems while balancing customer needs, quality, speed, and risk.

Own the strategy and roadmap for Affirm’s consumer credit experiences across shopping, repayment, and marketing. Lead discovery, experimentation, personalization, and cross-functional execution with Engineering, Design, Analytics, Credit, Marketing, Commercial, and Legal teams. Translate complex credit capabilities into intuitive consumer journeys, including prequalification and purchasing power experiences. Define success metrics and improve activation, conversion, repeat engagement, comprehension, and responsible access to credit.

Build and maintain GTM data pipelines, marts, semantic models, and dashboards supporting headcount planning, quota attainment, pipeline, and sales effectiveness. Partner with GTM analysts and stakeholders to establish trusted metrics, document data systems, enable self-service analytics, and develop AI-powered natural-language data tools. Translate complex data concepts for executives and engineers while advancing the GTM data roadmap.

Own the strategy, roadmap, delivery, pricing, and growth of Sprout Social’s Listening product. Drive adoption and competitive differentiation through customer discovery, market analysis, product investments, and cross-functional collaboration with Engineering, Design, Marketing, Sales, Customer Experience, and GTM teams. Establish success metrics, optimize usage and pricing opportunities, communicate product direction, and lead roadmap execution across distributed teams.

Build, maintain, and optimize responsive, conversion-focused websites, landing pages, and campaign assets. Translate marketing and design objectives into accessible, high-performing web experiences using HTML, CSS, JavaScript, and CMS platforms. Collaborate with marketing, design, SEO, and content teams; support CMS templates, integrations, forms, analytics, A/B testing, troubleshooting, technical SEO, and performance optimization.

Leads global total rewards strategy and an eight-person team across compensation, equity, benefits, retirement, executive compensation, job architecture, pay equity, governance, and HR technology. Advises executives, boards, and Compensation Committees; oversees scalable programs, international expansion, audits, acquisitions, and public-company readiness. Partners with Finance, Legal, and external advisors while advancing analytics, automation, AI, and platforms such as Pave.

Lead Android technical direction and build Kotlin experiences focused on user growth and subscription revenue. Partner with Growth, Marketing, CRO, and Sponsorships to run experiments, improve conversion, and enable self-service marketing tools. Own the mobile marketing technology stack, funnel instrumentation, analytics, feature flagging, safe rollouts, performance, accessibility, architecture, and code quality for a consumer app serving millions of readers.

Build and manage scalable partner marketing programs that generate demand and pipeline. Own partner segmentation, messaging, joint campaigns, partner enablement, budget allocation, and MDF investments. Measure partner-sourced and partner-influenced pipeline, engagement, and ROI while coordinating with Channel, Demand Generation, Product Marketing, Sales, Content, and Revenue Operations. Improve workflows through AI and automation in a fully remote, global environment.

Own the strategy, roadmap, and business outcomes for mid-market customer experience products serving businesses and BPO operators. Lead customer discovery, prioritize omnichannel and AI-powered capabilities, partner with cross-functional teams through delivery and launch, establish success metrics, drive adoption, and influence executives through data-driven recommendations. Focus areas include shared inboxes, agent workspaces, workflow automation, routing, analytics, and customer interaction platforms.

Leads complex enterprise sales cycles for Workday platform, data, analytics, AI, and extensibility solutions. Builds executive relationships with CIOs and CTOs, develops account strategies and pipeline, translates technical priorities into business value, and coordinates presales, product, customer success, partner, and sales teams. The role requires selling complex SaaS solutions, closing large multi-stakeholder deals, and collaborating with cloud, systems integration, and technology ecosystem partners.

Architect and own marketing data infrastructure, including Databricks pipelines, Gold Layer tables, semantic models, and trusted analytics foundations. Lead cross-functional data initiatives, translate ambiguous business needs into scalable solutions, improve reliability and quality, and mentor engineers. Build and monitor production LLM and agent systems, automate workflows with AI, and deliver high-quality Python and SQL while validating AI-generated code. Partner with Marketing, Sales, BI, Data Science, and R&D teams.

Designs and delivers Master Data Management solutions for consulting clients. Defines solution architecture, data models, governance strategies, integrations, infrastructure, testing, and performance optimization. Advises business and technology teams, leads internal and partner resources, coordinates with project managers, conducts solution reviews and training, and supports implementation across multiple client engagements. Requires substantial MDM, Syndigo PIM, Java, database, consulting, project leadership, and business analysis experience.

Develop and maintain relationships with existing medium enterprise customers, driving add-on sales and renewals of Workday solutions. Responsibilities include account planning, strategic deal management, C-suite negotiations, long-term account strategy, and coordination with presales, marketing, technical, and sales support teams. The role focuses on consultative SaaS and cloud solution selling through extended sales cycles and large enterprise deals.

Owns and expands strategic Energy and Infrastructure client relationships, driving account growth through consultative selling, solutioning, and cross-sell opportunities. Provides energy-sector leadership across generation, transmission, utilities, and LNG. Leads large engagements from solution definition through delivery while partnering with sales, consulting, technology, and delivery teams. Develops reusable offerings, practice capabilities, thought leadership, and go-to-market strategies for the portfolio.

Leads global marketing operations, technology, AI and automation, website operations, analytics, data governance, measurement, and digital experience strategy. Owns marketing technology investments, operating models, budgets, transformation initiatives, executive dashboards, attribution, and cross-functional alignment. Builds and manages a high-performing team while partnering with Marketing, Sales, Revenue Operations, Product, Technology, Data, Finance, and Legal.

Analyze investment risk outputs, identify patterns and anomalies, and develop actionable insights. Support risk metric production, reporting, workflow monitoring, data-quality improvements, and automation of analytics processes. Collaborate with Business Technology teams and external vendors, document methodologies, and help enhance scalable risk-management capabilities using quantitative analysis, programming, and emerging technologies.

Design, develop, and support business applications, automations, and AI-enabled solutions. Build full-stack applications, prototypes, and production systems using modern cloud, DevOps, and generative AI technologies. Collaborate with stakeholders, architects, data teams, and infrastructure teams to deliver secure, reliable solutions. Support applications throughout their lifecycle, contribute to engineering standards, troubleshoot production issues, and mentor developers within Agile delivery processes.

Develops revenue analytics, business intelligence solutions, data models, automated pricing and inventory tools, reports, and decision-support systems. Translates Revenue Management and Pricing business problems into actionable insights, supports system migrations and administration, conducts testing, automates routine processes, and represents the business on cross-functional projects. The role requires strong SQL, database, OLAP, ETL, communication, and project coordination skills.

Build and operate scalable analytics data platforms using Java, Python, Spark, Airflow, Iceberg, and AWS. Responsibilities include developing batch pipelines, automated testing frameworks, CI/CD validation, data quality controls, representative test datasets, and release gates. The role also advances AI-driven engineering workflows, supports production reliability through on-call participation and incident analysis, and collaborates with distributed engineering teams to improve platform quality, scalability, and observability.

Owns analytical projects across customer onboarding, transaction behavior, and platform operations. Designs dashboards, KPI frameworks, reporting workflows, and data pipelines while delivering actionable insights. Partners with Engineering, Product, Payment Operations, Compliance, and Finance; mentors colleagues; manages project scope and priorities; resolves ambiguity; and drives cross-functional alignment. Requires advanced SQL and data modeling skills, BI tool experience, analytical scripting familiarity, FinTech domain knowledge, and 4+ years of analytics experience.

Own end-to-end digital media campaigns across DV360, CM360, YouTube, Meta, and TikTok. Responsibilities include campaign setup, trafficking, QA, tracking, Floodlight implementation, pacing, programmatic optimization, PMP and audience activation, reporting, testing, and client recommendations. The role requires troubleshooting tracking issues, analyzing performance data, automating reports, and collaborating with internal teams and publishers. It is fully remote across the U.S. and Canada, with occasional travel for company events.

Build production-grade forecasting, simulation, causal inference, Bayesian, and probabilistic models supporting customer retention, expansion, adoption, and business planning. Partner with Success, data engineering, and platform teams to integrate models into operational workflows. Own the full model lifecycle, including feature engineering, deployment, monitoring, validation, back-testing, explainability, and tuning. Translate complex business systems into scenarios, insights, and recommendations for executive decision-making.