Top Data Jobs in Ottawa

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, design A/B and bandit experiments, develop pricing automation (DealBot) and monitoring for AI-driven rate recommendations, own ETL/analysis/visualization, and partner with Finance, Risk, Product, and GTM teams to operationalize pricing intelligence.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

In this role, you will define and execute the go-to-market strategy, drive growth, and lead customer success efforts at Reflow, a workplace intelligence platform.

As a Product Manager at Reflow, you will lead product strategy, execution, and delivery while ensuring customer engagement and managing engineering dependencies in an early-stage startup environment.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.

Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met.

Design, build, and scale real-time and batch data infrastructure and pipelines (Kafka, Databricks, Snowflake) to power analytics, reporting, and AI-powered data experiences. Drive data modeling, governance, observability, and best practices while partnering with cross-functional teams and mentoring engineers.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

Lead executive interviews, stakeholder workshops, and current-state assessments to identify operational gaps and opportunities. Develop business cases, operating models, governance, KPIs, roadmaps, and practical AI-enabled solutions. Advise on AI strategy, innovation, commercialization, customer experience, and change management. Support transition of recommendations to delivery teams and occasionally participate in business development.

Design, build, and operate production AI systems and marketing data infrastructure. Develop retrieval pipelines, agent orchestration, CDP integrations, ETL/ELT pipelines, and analytics. Automate workflows with AI, ensure data quality and reliability, partner with stakeholders, ship Python and SQL code, mentor engineers, and drive requirements to production.

Build and ship end-to-end ML/AI systems (traditional ML, NLP, LLMs/AI agents) on transaction, merchant, and location data. Prototype, productionize, and monitor models, collaborate with engineering and product, and (for senior hires) shape roadmap and mentor teammates.

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.

Develop and maintain ETL processes and data pipelines using SSIS and Microsoft Fabric. Design workflows for extracting, transforming, and loading data; ensure data quality, integrity, and availability; collaborate with analysts on modeled data, dashboards, and reports; and troubleshoot existing integrations. The role requires SQL expertise, ETL and data modeling knowledge, analytics collaboration, and eligibility for Controlled Goods and Level II NATO Secret clearance.

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.

Coordinates corporate security operations and projects from planning through close-out. Supports project management, security design, data analysis, screenings, policy development, site inspections, technical troubleshooting, and hardware/software testing. The role requires coordinating competing priorities with architecture, engineering, construction, security, and procurement experts, working onsite in operational and construction environments, obtaining Top Secret clearance, and supporting flexible hours, occasional overtime, and potential travel throughout Canada.

Lead options analysis and systems definition for an Intelligence Mission Data project: gather and trace business requirements, develop system use cases and specifications, evaluate technical solutions, plan organizational impacts, support integration and testing, and prepare briefings and project documentation.

Owns the design, delivery, and sustainment of infrastructure, tooling, automation, CI/CD, observability, security, and governance for Assent’s Data & AI Platform. Builds scalable AWS infrastructure supporting Snowflake, dbt, Airflow, data pipelines, warehousing, and AI/ML workloads. Partners with Data Engineering to reduce operational friction, establishes incident-response practices, and guides teams on deployment and infrastructure best practices while contributing to broader DevOps standards.

Design, build, and maintain robust terabyte-scale data pipelines and stream-processing applications. Collaborate with product teams, participate in full SDLC, automate tests and deployments, monitor operations, and contribute to technical strategy and continuous improvement. Participate in on-call rotation.

Designs, develops, and implements secure, scalable, high-performing data platforms and workflows. The role shapes data engineering architecture and technology decisions, establishes coding standards, conducts code reviews, and performs hands-on engineering. It collaborates with database, software, product, and AI/ML teams, improves data delivery processes, mentors engineers, and aligns data initiatives with business objectives.

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.

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.

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.