Top Data Analyst Jobs in Ottawa

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Lead marketing analytics and data strategy for B2B SaaS Marketing. Design measurement frameworks, own attribution, funnel and lifecycle analysis, forecasting, and marketing investment recommendations. Partner with senior marketing leaders and cross-functional teams to build data foundations, enable AI-assisted analytics, and mentor analysts to raise analytical standards.

Analyze observability, digital experience, and business analytics data for enterprise clients. Manage client relationships, conduct ad hoc analysis, configure Dynatrace solutions, create reports and dashboards, present findings to technical and executive audiences, train users, and translate performance insights into business outcomes. Represent client needs to Dynatrace product teams, influence roadmap decisions, and help improve internal processes and training.

Own GTM data accuracy, hygiene, governance, and integrity across Salesforce and related systems. Build data models, pipelines, Power BI or Tableau dashboards, and automated reporting for Sales and executive stakeholders. Analyze pipeline, forecasting, conversion, win/loss, productivity, and eventually Customer Success metrics. Document KPI definitions, train users, resolve workflow bottlenecks, and recommend improvements to data architecture and processes.

Analyzes pipeline, funnel conversion, campaign performance, retention, and revenue drivers across Sales, Marketing, and Client Success. Builds and maintains dbt models, data marts, quality controls, documentation, and BI-as-code assets using Salesforce and modern data-stack technologies. Partners with stakeholders to turn ambiguous questions into decisions and advances AI-agent workflows for faster analytics and reporting.

Analyze large datasets to produce dashboards, metrics, and insights supporting product, care, and business decisions. Build BI infrastructure, run A/B and multivariate tests, perform ad-hoc analyses and visualizations, and collaborate with stakeholders and data scientists to inform strategy and operations.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Analyze user behavior and product performance, create reports and dashboards, and provide data-driven insights to teams for decision-making.

Analyze player behavior, game health, engagement, retention, monetization, and live-service performance for Marvel Strike Force. Own KPI reporting, explain trends and variances, evaluate experiments, validate analytics tracking, and deliver actionable insights to product, design, marketing, live operations, and leadership teams. Use SQL, Python, reporting tools, and AI-enabled workflows while maintaining data quality, privacy, and analytical rigor.

As a Data Analyst at Stripe, you'll build data products, metrics, and dashboards, analyze large datasets, and communicate insights to drive business decisions.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

As a Data Analyst, you will analyze user behavior and product performance, creating reports and dashboards to aid decision-making and optimize user experience.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

Analyze go-to-market performance across marketing, sales, revenue operations, and finance. Build reporting connecting campaigns to pipeline and revenue, investigate funnel and attribution questions, support budget analysis and planning, improve data quality, and communicate insights to technical and non-technical stakeholders. Collaborate with AI and Data Engineering teams on marketing data agents, architecture, and source tables.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

The Product Data Analyst will analyze operational data, develop analytics frameworks, create dashboards in Tableau, ensure data integrity, and collaborate across teams to enhance decision-making and reporting.

Supports the analysis and definition of an Intelligence Mission Data project for a defence client. Gathers and documents requirements, facilitates use-case workshops, develops system specifications and traceability, evaluates technical alternatives, assesses organizational impacts, and supports solution testing and integration. The role also prepares briefings, meeting documentation, action reports, and progress updates while collaborating with users, customers, stakeholders, and project staff.

Lead product analytics for usage, activation, adoption, retention, and expansion. Define metrics, improve instrumentation, build reusable measurement frameworks, apply AI-first analytics workflows, design experiments and observational analyses, create monitoring/alerting, surface insights to influence product decisions, and mentor analysts.

Lead options analysis and systems definition for an Intelligence Mission Data project: gather and trace business requirements, develop system use cases and specifications, evaluate technical solutions, plan organizational impacts, support integration and testing, and prepare briefings and project documentation.

Build and maintain financial and operational datasets and Power BI dashboards; map metrics across eCommerce and engineering sources; support AOP, ARR, pricing and retention modeling; run CI/CD pre-production checks, monitor processes, and partner cross-functionally with Finance, Marketing/Retention, and Product.

Support D2C and B2B growth by building automated dashboards, performing funnel and conversion analyses, tracking lifecycle marketing and ad performance, and partnering with cross-functional teams to scale growth initiatives. Learn from mentors and progress into owning growth and marketing analytics domains.

Drive product and performance analytics for mobile app user acquisition: define core metrics, analyze campaign and product trends, build dashboards and data pipelines, support experiments and ML teams, automate reporting (including AI-powered workflows), and communicate findings and recommendations to stakeholders.

Build and maintain the product analytics data foundation: design scalable dbt models, define semantic models and governed metrics, partner with Engineering on instrumentation, certify datasets for BI tools, monitor pipelines and data quality, and use AI to accelerate analytics engineering workflows.

Lead the data solutions strategy for PR&C PSP division, managing data initiatives, teams, and collaborating on analytics projects. Ensure compliance, governance, and optimize data services while communicating technical solutions to stakeholders.