Top Data Analyst Jobs in Ottawa

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.

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

Senior Data Analyst partnering with Marketing to measure attribution, funnel performance, forecasting, and lifecycle metrics. Build analytical frameworks, scale AI-assisted analytics, work with cloud data stacks, BI tools, and martech to inform marketing decisions and improve data foundations.

Lead BI analyst leveraging a modern data stack to deliver dashboards, automated reports, and AI-driven insights. Partner with stakeholders to define data needs, build Tableau visualizations, write complex SQL in Snowflake, and integrate Snowflake Intelligence/Claude to automate workflows and enable self-service analytics across the company.

Perform product and player-behavior analysis for Marvel Strike Force using SQL/Python and reporting tools. Build recurring KPI reports, design/validate analytics tracking and experiments, partner with cross-functional teams, and use AI-enabled tools to accelerate workflows while ensuring data quality, privacy, and clear executive-ready insights.

Support international data initiatives by performing SQL-based analysis, producing insights and executive-ready scorecards, maintaining reporting/operational dashboards, coordinating incident management and operational readiness, and aligning cross-functional stakeholders to drive data-driven decisions across global markets.

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 Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

The MDM Data Analyst will translate business needs into data requirements, document governance rules, and ensure high-quality master data management across enterprise systems.

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

Manage and optimize the university CRM and its data to ensure integrity, governance, and effective system use. Perform data analysis, reporting, dashboarding, and BI to deliver actionable insights. Support stakeholders, develop KPIs, maintain documentation, ensure compliance, and drive continuous improvement of data processes.

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.

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

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 Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.

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.

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.

As a Senior Data Analyst, you will support Finance and Payments teams by building SQL/dbt models, creating Looker dashboards, and providing actionable financial insights.

The Data Analyst will support business needs through technical problem-solving and data analysis, focusing on improving user experience and conversion rates in a B2B2C environment.

Lead end-to-end debit analytics: design and modernize reporting, build executive dashboards, run A/B tests, produce actionable insights, optimize measurement/KPIs, mentor analysts, and partner with stakeholders to influence product and business decisions using cloud data platforms and advanced SQL/Python analytics.

Perform systems analysis and options analysis for an Intelligence Mission Data project: gather and translate business requirements into system specifications, develop use cases, evaluate technical solutions, ensure integration with business processes, support testing, and prepare reports, briefings, and meeting artifacts for project stakeholders.

The Robot Data Operations Analyst will control robots, evaluate performance, provide quality assurance, and document observations safely in an R&D setting.

Lead people analytics by building end-to-end models and production data pipelines, designing dimensional models, and creating LLM/NLP solutions. Translate statistical outputs into executive-ready insights, develop automated dbt/Snowflake workflows and dashboards, partner with HR systems owners and the enterprise data office, and enforce data governance and privacy for People data to support strategic workforce decisions.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.