Top Data Jobs in Ottawa

Lead product marketing for Procore AI & Data products: own positioning, messaging, launches, competitive positioning, sales enablement, and cross-functional GTM programs. Collaborate with Product, Demand Gen, Sales, and global Marketing to create customer-facing content and drive adoption.

Analyze, validate, and standardize community health data; identify trends, outcomes, quality issues, and impact indicators; improve collection and reporting practices; and translate findings into accessible reports, visualizations, communications, advocacy materials, and funding applications. The role collaborates with multiple member organizations, supports program evaluation and impact measurement, protects confidential information, and contributes to logic models, work plans, outcome measures, policies, and data practices.

Supports the analysis and definition of an Intelligence Mission Data project for a defence client. Gathers and documents requirements, facilitates use-case workshops, develops system specifications and traceability, evaluates technical alternatives, assesses organizational impacts, and supports solution testing and integration. The role also prepares briefings, meeting documentation, action reports, and progress updates while collaborating with users, customers, stakeholders, and project staff.

Leads the enterprise data and integration capability by developing strategy, architecture, governance, standards, roadmaps, and operating models. Establishes scalable APIs, data pipelines, event-driven integrations, metadata, lineage, master data, and quality practices. Provides strategic leadership for data platforms, analytics, AI readiness, and modernization; evaluates technologies and vendors; leads a Data Engineering team; and partners with business, technology, cybersecurity, infrastructure, and external stakeholders to improve enterprise data delivery and governance.

Leads the enterprise data and integration function by developing strategy, architecture, governance, standards, roadmaps, and scalable data capabilities. The role oversees integration architecture, APIs, data platforms, pipelines, metadata, data quality, analytics, AI readiness, and modernization. It also leads a Data Engineering team, evaluates technologies and vendors, establishes governance, reduces technical debt, and partners with business, cybersecurity, infrastructure, applications, and architecture leaders.

Designs and deploys data integration, data management, reporting functionality, and data models for insurance-sector transformation projects. The role analyzes client needs, configures SAP solutions, applies data modeling expertise, and collaborates with software development and sales teams. Candidates need experience with IT transformation, insurance data processes, SAP FDS or SAP BW solutions, SAP HANA technologies, and technical mapping. The position is Canada-based with 50% travel and occasional on-site work in Calgary or Toronto.

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.

Explore large-scale AI evaluation datasets, identify patterns, biases, and causal relationships, and design experiments to understand model behavior. Build reproducible analysis pipelines with Python, Pandas, NumPy, and Spark; develop statistical and causal inference frameworks; partner with ML researchers and engineers; and communicate findings to technical and non-technical stakeholders.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

Lead enterprise data architecture and transformation initiatives for financial-services clients. Responsibilities include defining target-state architectures, operating models, roadmaps, integration patterns, data governance, platform strategies, and architectural standards. The role evaluates vendors and build-versus-buy decisions, leads workshops and delivery teams, communicates with executives, manages complex projects, develops internal intellectual property, and mentors consultants. Strong expertise in MDM, data modeling, integration, cloud data platforms, governance, quality, security, and asset and wealth management data is required.

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

Own Orum’s data platform architecture, roadmap, reliability, and scalability. Build batch and real-time ETL/ELT pipelines using PostgreSQL, event streams, ClickHouse, BigQuery, and dbt. Administer Looker and develop LookML models, dashboards, and a trusted semantic layer. Establish data quality, governance, lineage, observability, and metric standards while partnering with Product, Finance, GTM, and Operations on analytics, AI, and business intelligence initiatives.

Own the vision and roadmap for Wrapbook’s Agreement Data Platform, including agreement data models, rules, APIs, operator tooling, validation, and governance. Partner with engineering and payroll teams on migrations, service boundaries, explainability, compliance, and reliable downstream calculations. Drive discovery through launch, define measurable success metrics, use data to prioritize decisions, and leverage AI tools daily for analysis, coding comprehension, writing, and prototyping.

Leads Medavie’s enterprise data, analytics, and AI strategy and program governance. Defines the multi-year roadmap, strategic guardrails, portfolio priorities, governance forums, decision rights, reporting, metrics, and value-realization practices. Partners with executives, business lines, IT, risk, privacy, and legal teams to align investments, manage strategic risks, promote responsible AI, and advance data and AI literacy across the organization.

Coordinate cross-functional programs across HR, Finance, and corporate functions from planning through execution. Manage employee lifecycle workflows, recruiting operations, compliance tracking, finance operations, audits, budgets, reporting, and leadership updates. Identify and implement AI-enabled workflows, translate processes into agent instructions, monitor accuracy and privacy, establish performance metrics, and train internal users. Partner with executives and functional leaders to improve operational processes and adoption of automation.

Lead product design for Waabi’s driverless commercial and operations ecosystem, including fleet management, remote assistance, dispatch, monitoring, and safety-critical workflows. Observe fleet operators and terminal staff, design human-AI interactions, extend the design system, and ship directly in React codebases using AI-assisted tools. Collaborate with product, engineering, research, and operations teams while helping establish design culture and processes as the second product designer.

Evaluate and annotate 3D meshes, GLB files, images, and short videos for model training and error resolution. Identify whether assets are artist-created or AI-generated, and detect geometry defects, topology errors, and scene inconsistencies. Requires hands-on 3D modeling experience, familiarity with Blender or Maya, strong mesh-topology knowledge, English proficiency, and a suitable computer with dedicated graphics capabilities.

Design and lead scalable data engineering solutions using Databricks and Azure. Establish enterprise data modeling and engineering standards, architect pipelines and integrations, improve platform reliability and performance, guide modernization and cloud migrations, troubleshoot complex issues, and mentor data engineers while ensuring security, quality, and governance.

Design, develop, and maintain scalable data pipelines, models, ingestion, transformation, and integration solutions using Databricks and Microsoft Azure. Troubleshoot performance and data quality issues, optimize workflows, support migrations and modernization, and collaborate with architecture and engineering teams. Translate business requirements into technical solutions while following security, governance, quality, and engineering best practices.

Build highly available, scalable distributed systems and real-time data services supporting Internet-wide scanning, DNS resolution, certificate ingestion, security research, and customer applications. Responsibilities include developing data pipelines, messaging systems, databases, caching layers, tooling, frameworks, and cloud or on-premises services; productionizing prototypes; and collaborating with engineering, product, machine learning, and security teams. The role emphasizes maintainable, testable code, reliability, monitoring, and long-term platform development.

Build highly available, scalable distributed systems and real-time services supporting Internet-wide scanning, DNS resolution, certificate ingestion, data pipelines, messaging, databases, caching, and APIs. Productionize prototypes, develop reusable tooling and platform capabilities, maintain cloud and on-premise systems, and collaborate with engineering, product, machine learning, and security teams.

Updates machine learning training and test datasets, refines annotation guidelines, initiates model training, and evaluates model performance. The role annotates synthetic text and image data, conducts manual quality analysis, identifies error patterns, reports anomalies, and produces findings on utterance quality, LLM evaluation, ASR bugs, and customer pain points. It also applies basic NLP and linguistic knowledge to ensure data accuracy and consistency.

Manage technical data for IP Routing hardware NPI programs: support NPI from data entry through factory implementation, maintain product data and Engineering Change Orders across the product lifecycle, and coordinate with engineering, supply chain, and manufacturing to ensure accurate PLM/PDM records and implementation.

Leads the design and delivery of scalable data pipelines, dbt models, orchestration workflows, and analytical data models. Establishes data architecture, engineering standards, testing, observability, governance, and quality practices. Partners with stakeholders to deliver data-driven solutions, supports incident response, and provides technical leadership through design reviews, mentorship, hiring, and team development.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.