Top Data Analyst Jobs in Toronto

Deliver accurate, timely workforce reporting and insights for HR and business partners. Maintain data quality, enforce reporting governance, automate recurring reports using Excel/Power Query, support HR systems (Dayforce/Workday/etc.), validate data, and partner with stakeholders to improve reporting processes and data literacy.

Support driver earnings and marketplace teams with SQL-driven analysis, reporting, and financial reconciliation. Provide insights, track product performance, support experiments, prepare leadership business reviews, and develop processes and playbooks to improve earnings products and reduce errors.

Support monthly reporting, budgeting, forecasting, and variance analysis for RDT. Produce and maintain financial reports, master data, and models to enable decision-making. Collaborate with finance and business partners, prepare leadership materials, perform ad-hoc analyses and scenario planning, and drive process improvements and automation using digital and AI solutions.

Lead the RTB reporting sub-team to ensure accurate, reliable finance and compliance reports. Build repeatable processes, documentation, and automation; own stakeholder relationships; mentor juniors; and drive cross-functional reporting initiatives from definition through execution.

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.

Lead investment data governance by designing and operating data quality controls, reconciling and troubleshooting investment system data, administering reference/security master and pricing data, managing vendors, supporting front-office/trading applications, and participating in system releases and MDM activities to ensure accurate, timely data for investment decision-making.

As a Data Analyst, you will support data migration initiatives by analyzing data structures, mapping source to target systems, and collaborating with stakeholders to document requirements and findings.

The Lead Financial Data Analyst manages financial instrument data collection, quality control, client inquiries, and operational risk compliance, while coaching others and improving processes.

As a Lead Financial Data Analyst, you will manage the collection, control, analysis, and distribution of financial data for clients, ensure compliance with SLAs, and guide process improvements.

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.

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 in People Analytics at Lyft, you'll manage data requests, build ThoughtSpot dashboards, and enhance insights using AI capabilities. You'll collaborate with HR to craft metrics and translate findings into actionable insights for leadership.

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.

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.

Design and maintain Azure DevOps CI/CD pipelines and automate deployment of Microsoft Fabric, Azure Data Factory, Synapse, Databricks, and Power BI. Implement IaC (Bicep/ARM), manage Azure environments, security, secrets, monitoring and logging, and collaborate with cross-functional teams to improve automation and platform delivery.

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.

Eight-month internship supporting data management and reporting within the Digital Product Management team. Collaborate with investment, trading, compliance, sales, HR and operations to gather requirements, document processes, produce BRDs/user stories, assist data analysis and reporting, and support deployment of data automation and reporting solutions. Gain exposure to Agile delivery and cross-functional project work.

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.

Support stakeholders by profiling, mapping, and validating financial reconciliation datasets. Build complex SQL queries and Python workflows, and use Snowflake and Databricks to design, transform, and manage large-scale finance data for reporting, reconciliation, and analytics. Ensure data quality, perform root-cause analysis, and support governance and documentation.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

The Lead Data Analyst role involves analyzing audience behavior and content performance, turning data into actionable insights, and supporting product strategy through data analysis.

Analyze complex datasets, build interactive dashboards, run predictive and statistical analyses, enforce data governance, automate reporting, and partner cross-functionally to deliver actionable insights.

Provide day-to-day Salesforce and Datalinx platform administration, maintain data quality (cleansing, deduplication, enrichment), support reporting and BI workflows, execute outbound campaigns, document processes, and assist integrations and operational analytics to ensure accurate, consistent, scalable platform operations.

Design and maintain ETL/ELT pipelines and semantic/analytical data models; extend metric layers for BI and LLM/RAG-driven natural-language analytics; apply AI/ML and data-science techniques to produce trusted investment metrics, insights, and recommendations; embed data quality, lineage, and governance; collaborate with investment, finance, and technology stakeholders to prototype and productionize AI-enabled reporting solutions.

Lead applications systems analysis and development for Big Data platforms. Partner with management to define enhancements, resolve complex issues, enforce coding/testing standards, coach mid-level developers, and ensure compliance and risk management.