Top Data Analyst Jobs in Montreal

Analyzes operational data using Python, Excel, SQL, Power BI, and Databricks to identify trends, anomalies, and process improvement opportunities. Builds and maintains dashboards, validates data across stakeholders and systems, performs root-cause analysis, and presents actionable findings to senior management. The role supports a lead analyst and focuses on hands-on analysis rather than architecture, engineering, or people management.

Coordinate client data migrations onto Computershare’s SCRIP platform, including requirements gathering, data inspection, mapping, validation, testing, business sign-off, and collaboration with developers and operations teams. Plan and configure large or extraordinary corporate actions while managing high-risk operational events, concurrent projects, stakeholders, change processes, and tight deadlines.

Designs, builds, maintains, and validates Sisense dashboards and tabular reports for customers. Translates complex business and compliance requirements into accurate reporting solutions, models data, troubleshoots production incidents, and ensures performance and consistency with application data. Collaborates with Product Owners, QA, engineering, data, and customer-facing teams to define requirements, validate results, maintain reporting standards, document solutions, and support agile delivery.

Supports public health data extraction, management, quality assurance, cleaning, validation, harmonization, documentation, and statistical analysis. Develops analytic datasets and performs qualitative, quantitative, and mixed-methods evaluations of program implementation and outcomes. Prepares technical memoranda, reports, tables, figures, and presentations, and communicates findings to program stakeholders. Requires knowledge of public health research, evaluation methods, government procedures, CDC administrative systems, and Microsoft Office.

Leads advanced data analytics for Tribal healthcare initiatives, including data resource inventories, quality assessment, linkage analysis, predictive and prescriptive modeling, reporting, dashboards, and large-scale analytics projects. Establishes data quality frameworks, supports federal compliance, coordinates cross-functional initiatives, and mentors junior analysts. Uses Python, R, SQL, statistical methods, machine learning, and data modeling to produce actionable insights and maintain data integrity.

Analyzes insurance business data, develops and optimizes business intelligence tools, supports risk management and market analyses, defines KPIs, and improves data quality and governance. The role translates business needs into documented solutions and advises partners on data opportunities. It requires collaboration with pricing, claims, and business teams, along with proficiency in SQL and Power BI or Tableau.

Analyze and document source data, business rules, functional specifications, data models, and ETL requirements for a large-scale Azure data platform. Support architects, developers, business experts, and QA through data profiling, Power BI platform configuration, test case creation, validation scripts, and execution. Quickly assume ownership of an ongoing project while managing complexity and meeting deadlines.

Leads HR data governance and information-management initiatives, analyzing processes and data flows, defining requirements, improving metadata and data quality, and remediating data concerns. The role establishes ownership and definitions in Collibra, embeds governance requirements into technology changes, creates guidance for HR teams, and communicates risks and recommendations to senior stakeholders across HR, governance, and technology teams.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Lead HR data capability delivery: translate business needs into functional specs and user stories, analyze HR/Workday data, design Workday reports, validate API integrations, triage data issues, and support testing and platform releases to enable workforce insights and AI-supported decisions.

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

Conduct product and user behavior analysis, define KPIs, build dashboards and models, and design and evaluate A/B and multivariate experiments. Partner with product, lifecycle, marketing, data, and engineering teams to generate insights, improve user experiences, inform feature launches, and support growth decisions.

Own end-to-end financial data analysis, including SQL and dbt data modeling, Looker dashboard development, data quality validation, reconciliation, and stakeholder-facing insights. Partner with Finance and Payments to support reporting, planning, revenue analysis, cost insights, and transaction-level analytics. Translate ambiguous business needs into reliable technical solutions while improving documentation, QA, modeling, and data architecture practices.

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.

Build and maintain BI dashboards, reporting tools, and automated data workflows. Analyze customer behavior, funnels, retention, engagement, and product adoption to deliver actionable insights across Product, Operations, Marketing, Finance, and Leadership. Use AI tools and APIs to improve analytics workflows, self-service exploration, data-quality checks, and insight generation while validating accuracy, privacy, and business impact.

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.

Demonstrate ERP reporting capabilities, analyze customer requirements, design SQL- and Excel-based reporting solutions, develop proof-of-concepts and customer reports, provide initial product support, and train clients, partners, and colleagues. The role also requires creating documentation, estimating project scope, and maintaining expertise in Velixo and integrated ERP systems.

Owns advanced reporting, dashboards, data analysis, KPI development, ETL requirements, and data quality initiatives for internal stakeholders. The role delivers recurring and ad hoc reports, builds automated workflows, documents data definitions and processes, communicates insights to senior leaders, and supports BI sprint planning. Strong SQL, data visualization, stakeholder communication, and systematic data quality problem-solving are required.

Design, build and maintain robust Databricks data pipelines and ETL processes on cloud (Data Lake/Lakehouse). Develop transformations in Python and Spark, apply data quality best practices, integrate CI/CD (Azure DevOps), document solutions, and participate in Agile rituals to support analytical platforms and decision-making.

Analyze and consolidate data from multiple systems, build scalable dashboards and executive reporting, define standardized metrics, ensure data quality, and translate complex datasets into actionable business insights. Partner cross-functionally with Sales, Marketing, Customer Success, Product, Finance, Operations, and Data Engineering to support decision-making and improve reporting 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.

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.

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.

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.