Top Data Jobs in Ottawa

Own end-to-end analytical functions for growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and influence product, growth, finance, and operations decisions. The role requires strong independent data analysis, first-principles problem solving, clear communication, and ownership of ambiguous business challenges.

Own the analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, communicate insights, and drive decisions and outcomes with cross-functional stakeholders. The role requires strong analytical thinking, independent problem-solving, persuasive communication, and end-to-end ownership of ambiguous business challenges.

Own end-to-end analytical work for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, experiments, and analyses; surface insights; communicate recommendations; and influence product, growth, finance, and operations leaders to drive measurable outcomes.

Own end-to-end data science for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; communicate recommendations; and drive decisions and measurable outcomes with cross-functional stakeholders.

Own end-to-end data science for growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires strong SQL or Python skills, independent analytical problem-solving, clear communication, and ownership of ambiguous, high-impact initiatives.

Build and scale real-time and batch data pipelines, data platforms, and analytics-ready datasets using Kafka, Databricks, Snowflake, Python, and SQL. Design modern data models, ensure data quality and observability, develop AI-powered data experiences, and support business-critical reporting and analytics. Collaborate cross-functionally, improve platform performance, champion engineering best practices, and mentor teammates.

Manage CRM customer data migrations from onboarding through completion. Responsibilities include analyzing source Excel data, creating import rules, validating and reconciling migrated data, documenting mappings and transformation logic, resolving discrepancies, and coordinating with customers, engineers, sales, onboarding, and support teams. The role requires strong Excel and Google Sheets skills, analytical problem-solving, attention to detail, customer service, and effective communication.

Lead enterprise client reporting and manage Proof’s data team. Own report accuracy, delivery, client relationships, data pipelines, shared models, BI tooling, and internal data insights. Coach team members, guide technical decisions, review SQL and data models, partner with Engineering and Product, resolve reconciliation issues, and improve automation. The role will establish data quality standards and help the company use trusted data to support growth, internal tools, and AI systems.

Coordinate customer onboarding, training, support, and retention workflows. Follow up on customer issues, align Sales, Accounting, Software, integrations, and licensing teams, and drive commitments through resolution. Build and improve operational processes, track projects, dependencies, blockers, and next steps, identify improvement opportunities from feedback, and provide clear updates across teams.

Supports the analysis and definition phase of an Intelligence Mission Data project. Gathers and documents requirements, facilitates workshops, develops use cases and system specifications, performs technical options analysis, evaluates solution compliance, assesses organizational impacts, and supports testing and integration. The role also prepares briefings, meeting records, action reports, and progress updates while collaborating with users, customers, stakeholders, and project personnel.

Build and maintain business-facing analytical applications, Tableau dashboards, reports, and Cube semantic models. Develop production code in Python and JavaScript, query Amazon Redshift, manage Salesforce reporting, and implement data quality validation, governance, access controls, and row-level security. Collaborate with cross-functional stakeholders to translate business needs into reusable data products, support data-driven decisions, and deliver projects through Git-based workflows, code reviews, and CI/CD.

Design, build, and maintain scalable data ingestion pipelines, databases and data lakes for credit and lending datasets. Ensure accurate data mappings, monitoring and alerting, translate stakeholder requirements into analytical data flows, and integrate APIs to deliver reliable, high-quality data products.

Build and operate Block’s data platform, including warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop reliable Python services, developer tools, and Terraform infrastructure for petabyte-scale data. Partner with data practitioners and product teams, establish engineering standards, provide technical direction, and mentor engineers while ensuring security, reliability, observability, usability, and data governance.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Build and own Snout’s data foundation, including PostgreSQL and dbt warehouses, ingestion pipelines, dimensional models, data quality, documentation, and reliable rebuilds. Reconcile data from veterinary practice-management systems, support LLM/AI tooling, translate stakeholder needs into technical plans, and establish the foundation for a future data team and analyst.

Design and lead enterprise data platforms, including scalable lakes, warehouses, batch and real-time pipelines, governance, quality, monitoring, and modernization. Build data infrastructure for production AI/ML systems, including embeddings, vector stores, RAG preparation, feature stores, and training and inference flows. Partner with leadership and cross-functional teams on data strategy, establish engineering standards, make architectural decisions, and mentor engineers.

Leads product marketing strategy, positioning, messaging, go-to-market execution, AI adoption, product launches, market expansion, and customer-driven roadmap input. Builds and manages a high-performing product marketing team, partners with executive, product, revenue, and marketing stakeholders, and drives product adoption, retention, category growth, and revenue across programmatic advertising and martech markets.

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.

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

Leads planning and roadmap execution for data orchestration capabilities across ingestion, transformation, routing, synchronization, monitoring, and delivery. Defines requirements for reusable pipelines, data contracts, schemas, lineage, observability, and AI-ready data flows. Partners with engineering, architecture, data, security, customer teams, and stakeholders to prioritize capabilities, improve reliability and adoption, reduce custom implementations, and establish measurable outcomes for data trust and onboarding efficiency.

Owns the strategy and roadmap for semantic insurance data products supporting AI, analytics, automation, and enterprise applications. Defines canonical concepts, relationships, metadata, data quality standards, APIs, knowledge graphs, and AI-ready consumption patterns. Partners with engineering, architecture, data, AI, UX, customer success, and insurance stakeholders to translate complex P&C insurance needs into product capabilities, prioritize use cases, establish requirements, drive adoption, and measure business impact.

Lead and develop five experienced analysts and data scientists while personally owning analytics across ecommerce, health, and supply chain. Partner with executives, establish KPI and reporting standards, prioritize the analytics roadmap, deliver strategic insights, and advance AI-native self-service analytics tools. The role combines people leadership, hands-on analysis, data governance, and business strategy in a remote-first environment.

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.

Provide Workday HCM data conversion consulting across client implementations and post-production projects. Build, validate, and deploy data conversion, business process, and reporting solutions; guide requirements, configuration, testing, and production deployment; collaborate with engagement and sales teams; maintain project forecasts; advise on Workday best practices; and support client relationships.

Own the strategy, roadmap, architecture, and adoption of the company’s central data infrastructure and BI platform. Partner with analytics, engineering, and business teams to establish trusted KPI reporting, semantic models, scalable warehousing, BI and ETL tooling, clear SLAs, and AI-powered self-service insights. Translate ambiguous needs into testable requirements, evaluate technical solutions, prototype quickly, and measure adoption, quality, and reporting efficiency.