Top Data Analyst Jobs in Montreal

Collects, processes, analyzes, and interprets data to support business decisions. Identifies stakeholder needs, develops and updates reports, improves data methods, advises on data management tools, validates analytical datasets, and provides recommendations. The role also supports data-related projects, operational initiatives, and stakeholder guidance across business functions.

Business Intelligence Data Analyst responsible for data profiling, warehouse solution design, impact analysis, technical documentation, SQL analysis, Power BI reporting, Microsoft Fabric semantic modeling, and data quality initiatives. The role bridges business processes, operational systems, and enterprise data warehouses while coordinating data engineers through integrations, migrations, and implementation. It also involves stakeholder management, business process analysis, and consulting on enterprise IT solutions.

Analyze data from multiple channels and databases, develop reporting and interpretation tools, identify process improvements, and advise stakeholders on complex analytical initiatives. Perform descriptive and diagnostic analyses, translate business needs into data solutions, coordinate implementation, and provide recommendations to support strategic decision-making.

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.

Supports data extraction, management, quality assurance, cleaning, validation, harmonization, statistical and qualitative analysis, and public health program evaluation. Develops analytic datasets and contributes to technical memoranda, reports, presentations, tables, and figures. Analyzes implementation measures and mixed-methods data, interprets findings, and recommends program improvements. Requires collaboration with government and public health stakeholders, use of Microsoft Office and CDC administrative systems, and the ability to obtain and maintain required customer clearance.

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.

Analyze financial and business data across ARR, retention, billing, subscriptions, and customer cohorts. Build interactive Hex dashboards, translate stakeholder questions into reporting, investigate financial variances, and automate recurring workflows using AI. Partner with Analytics Engineering to improve data models, reporting sources, data quality, and metric definitions. Present insights and collaborate with Finance, Sales, Marketing, RevOps, and Data and Analytics teams.

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.

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.

Analyzes business needs and data management initiatives within large-scale transformation projects. Partners with stakeholders to define requirements, facilitate workshops, model processes, assess change impacts, translate business rules for technology teams, support product backlogs and testing, and contribute to optimized solutions and continuous improvement.

Collects, extracts, analyzes, interprets, and validates data to support business decisions. Develops and maintains management indicators, reports, data analytics solutions, quality-control procedures, documentation, and training materials. Participates in SAS ETL development, supports data governance and publication quality, and assists users with data requests and interpretation.

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.

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

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.

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.