Top Data Jobs in Ottawa

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Lead the Public Sector sales team, achieve quotas, implement sales plans, forecast revenue, and cultivate customer relationships.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Intern will build enterprise data foundations and AI agents connecting LLMs to authoritative business knowledge. Responsibilities include developing retrieval/RAG pipelines, agent workflows, persistent memory/state management, governance controls, auditability, and integrations with vector DBs, knowledge graphs, enterprise tools, and multiple LLM providers.

Design, build, and scale Snowflake ingestion pipelines and ML/LLM systems. Create agentic tooling to generate, test, and maintain pipelines. Collaborate with analysts, data scientists, and product teams to deliver reliable, high-performance data infrastructure and operationalize models for an AI-first e-commerce platform.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Drive technical pre-sales for Microsoft cloud database and analytics solutions via demos, PoCs, hackathons, and architecture workshops. Design secure, scalable data architectures, resolve technical blockers, collaborate with engineering, and evangelize Microsoft Fabric, Azure Databases, Databricks, Purview and EDW migrations to accelerate customer adoption.

Lead design, development, and optimization of enterprise data solutions. Build and maintain data pipelines, warehouses, and analytics platforms. Apply data governance, quality, metadata, and lineage practices. Ensure data security and compliance, monitor platform performance, and collaborate with stakeholders while providing technical guidance and mentorship.

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.

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 enterprise semantic models and AI-ready data products, build and optimize Power BI datasets and DAX metrics, enforce governance and security, enable self-service and AI-assisted analytics, and collaborate with stakeholders and data engineers to support BI and ML integrations.

Lead AdRise data science initiatives to define experimentation, core KPIs, and measurement. Build production analytics and ML systems for targeting, pricing, and auction performance. Set technical direction, mentor data scientists, partner with Product and Engineering, and establish scalable data foundations and reproducible workflows to drive monetization.

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.

Evaluate and label model-generated and human-written code outputs, debug and assess code/agent trajectories, prompt models for complex data science tasks, review visualizations, and report quality trends to improve model behavior.

Lead advanced analytics projects to build, validate and monitor predictive and descriptive models. Determine technical approaches, evaluate diverse data sources, translate findings for stakeholders, and provide technical leadership and mentorship to analytics teams to support business decisions and risk mitigation.

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.

Design and implement data platform architecture, ETL/ELT pipelines, data mappings/lineage and quality rules. Build orchestration workflows, support data migration and CBM initiatives, deploy and monitor AI/ML models, and collaborate with analysts and stakeholders to deliver production-ready data solutions.

Lead data architecture for a Justice Information Management System modernization: consolidate reporting marts into an EDW, perform data profiling and modeling, develop ETL (SSIS), ensure data quality and governance, validate reporting, and communicate with stakeholders.

Design and define enterprise data architectures and logical/physical data models using Kimball dimensional modelling; develop models with PowerDesigner; work with JOIN and JIMS; ensure alignment with information management, cybersecurity, privacy, and data governance; communicate technical concepts to technical and business stakeholders; support modernization initiatives.

Lead product design for Stripe's Data & AI products, shaping systems and new products from ambiguous strategic problems to detailed interaction design. Collaborate cross-functionally with PMs, engineers, and design leaders to build trust-focused, end-to-end experiences and design systems.

Lead product analytics for usage, activation, adoption, retention, and expansion. Define metrics, improve instrumentation, build reusable measurement frameworks, apply AI-first analytics workflows, design experiments and observational analyses, create monitoring/alerting, surface insights to influence product decisions, and mentor analysts.

Lead presales engagements to design enterprise data platforms and governance on Microsoft Fabric and Azure Databricks. Conduct discovery workshops, architect governance with Purview/Unity Catalog, define AI-readiness and Copilot access, author proposals/RFP responses, run POCs/demos, and partner with sales and delivery teams to size and transition engagements to managed services.

Lead product vision and roadmap for Imogen Data, a platform that captures and transforms legacy system data. Collaborate with engineering, sales, marketing, and customer-facing teams to prioritize investments, drive execution, mitigate risk, and represent the product to stakeholders and customers. Evolve the product from MVP to enterprise scale while balancing strategy, delivery, and customer value.