Top Analytics Jobs in Vancouver

Own full sales cycle for Southern California enterprise accounts: source and close new logos, build executive relationships, run ROI-driven POCs, collaborate with Sales Engineering, and meet ARR targets through repeatable, metric-based sales strategies.

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.

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.

Lead operational execution of eDiscovery workflows from intake through production and case closure. Manage collections, processing, hosting, Relativity workspaces, review/analytics, vendor relationships, QA, and billing to ensure efficient, defensible discovery support for litigation teams.

Build and own the analytics foundation: maintain dbt models and Snowflake, create ELT pipelines (Python/Airflow), design semantic layers, ensure data quality and reconciliation, enable self-serve analytics and measurement for cross-functional teams, and support AI-ready data infrastructure.

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.

Leads data operations, analytics, merchant and regulatory reporting teams. Owns semantic-layer metric definitions, data governance, BI adoption, reporting accuracy, OKR instrumentation, and data automation. Partners with engineering, data science, product, actuaries, and executives to translate business needs into trusted data solutions. Builds team capability, improves data literacy, and drives cross-functional accountability across technical and business teams.

Lead product design for Stripe's Data & AI products, shaping systems and new products from ambiguous strategic problems to detailed interaction design. Collaborate cross-functionally with PMs, engineers, and design leaders to build trust-focused, end-to-end experiences and design systems.

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.

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 and scale client-facing data transformation pipelines for financial and operational data. Build reliable analytical models, data integrity tests, and integrations across diverse sources. Partner with Customer Success and Engineering to troubleshoot data issues, optimize critical pipelines, establish engineering standards, and improve developer experience. Use dbt, SQL, Python, BigQuery, and AI-enabled workflows to deliver performant, well-documented FP&A data products while mentoring teammates and contributing to hiring and onboarding.

Lead deployment and sustainment of a production operating system across the full biomanufacturing value stream. Perform diagnostics, build tiered daily management, run kaizen events, mentor teams in Lean problem-solving, connect performance to throughput and release readiness, and embed durable standard work and KPI governance.

Serve as a strategic analytics advisor to clients: design and audit Adobe Analytics and CJA implementations, run measurement workshops, build dashboards and reports, translate data into actionable stories, present findings, and enforce information security and data privacy best practices.

Lead development of scalable data products for Revenue: design dbt models, metrics, dashboards, governance, and AI enablement. Drive data architecture, quality, lineage, documentation, and automation; mentor analysts and align stakeholders to deliver reliable revenue analytics and reporting.

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

Serves as a strategic analytics partner to Marketing, owning funnel, attribution, ROI, account scoring, experimentation, and pipeline analytics. Builds scalable datasets, dashboards, and quality controls while connecting customer, campaign, product usage, CRM, and revenue data. Delivers executive-ready reporting, QBR insights, and recommendations that improve conversion, marketing investment effectiveness, account-based marketing, product adoption, and pipeline growth.

Lead and scale a global engineering organization to deliver enterprise-grade AI/GenAI SaaS products. Define technology strategy and roadmap, drive architecture for LLMs/RAG/NLP systems, ensure scalability/reliability, establish DevOps and quality practices, partner with Product/Sales/Customer teams, and manage hiring, budgets, and leadership development.

The Analytics Engineer partners with business stakeholders and data teams to translate reporting needs into scalable analytics solutions. Responsibilities include integrating disparate datasets, developing optimized SQL queries and reporting tables, improving data models, building executive dashboards and KPI frameworks, maintaining semantic-layer definitions and governance standards, and applying software engineering practices such as version control, continuous integration, and code reviews. The role also provides actionable business insights and supports evolving analytics requirements.

Build and own scalable data models for PlayStation game analytics, supporting new title launches and efficient, consistent querying. Collaborate with game studios and analysts to design and validate in-game telemetry, translate business needs into data solutions, and expand use of dbt and Airflow. Prioritize performance, consistency, quality, testing, and repeatable database development across analytics platforms.

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.

Build, operate, and extend Affirm's data platform and application tooling to enable self-service data applications at scale. Implement platform features (provisioning, CI/CD, access control), integrations, data governance, automation, observability, and on-call operations. Contribute to roadmap for semantic layers, agentic data tooling, and AI-native workflows while raising engineering and operational standards.

The Founding Account Executive will build and maintain a pipeline of mid-market or enterprise clients, managing deals end-to-end, leading proof-of-value motions, and defining sales strategies for growth.

Lead end-to-end solution design and architecture for Sales Cloud, Service Cloud, and Agentforce implementations. Translate sales and service requirements into scalable Salesforce solutions, define automation and AI use cases, oversee integrations, and drive governance, adoption, and measurable business outcomes while mentoring delivery teams and facilitating stakeholder workshops.

As a Software Engineer, you'll build scalable micro-services, work with large data sets, and optimize performance, focusing on distributed systems and real-time analytics.

Lead research, design, and implementation of large-scale cloud data ingestion, preprocessing, distributed training, and benchmarking for geospatial foundation models focused on agriculture. Contribute to model architecture, fine-tuning, tooling, documentation, and Agile development processes.