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.

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.

The Software Engineer will manage data collection for model training operations, enhance cloud infrastructure, and collaborate with AI scientists to improve data quality and scale.

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

Lead Andela Academy, scaling enterprise learning solutions in AI and Cloud. Build relationships, oversee team delivery, and drive revenue growth with high client satisfaction.

As the Senior Data Scientist for AI & Model Risk, you will lead AI risk assessments, coordinate with stakeholders, evaluate AI system designs, and ensure compliance with risk management principles in financial services.

Manage and optimize the university CRM and its data to ensure integrity, governance, and effective system use. Perform data analysis, reporting, dashboarding, and BI to deliver actionable insights. Support stakeholders, develop KPIs, maintain documentation, ensure compliance, and drive continuous improvement of data processes.

Design, build, and operate scalable cloud-native data platforms and production-grade pipelines using Azure, Microsoft Fabric, and Databricks. Implement lakehouse/medallion architectures, transform data with SQL/PySpark/Python, enable BI and AI workloads, enforce data quality, governance and security, automate deployments with DataOps/IaC, optimize costs, produce runbooks/docs, and mentor junior data engineers.

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.

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.

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.

Lead a hands-on engineering team to design, build, and operate the AI platform and orchestration layer for Hootsuite Analytics MCP. Own reliability, scalability, observability, and quality of routing, agent infrastructure, and data pipelines. Set technical direction, mentor engineers, drive architecture decisions with senior leaders, and ensure integrations with context and semantic layers for dependable AI-driven analysis at scale.

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 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.

Lead analytics for Internal Audit Claims: extract, transform, reconcile, and validate large claims datasets; build and maintain Power BI reports/dashboards; perform QA and tie-outs; support automation, bots/AI enablement, and executive reporting; mentor other analysts and partner with audit, IT, and business stakeholders to deliver repeatable, validated analytics.

Lead clinical data management from start-up to database lock for oncology studies, manage sponsor relationships, timelines, budgets, and junior DM staff; coordinate with biometrics, EDC, SAS, statistics and PK teams; identify risks/mitigations and ensure GCP/SOP compliance.

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.

Design, build, and maintain scalable data systems and ETLs on GCP; connect production data to business systems; generate analytics and ML-driven insights for GTM teams; work cross-functionally and introduce modern tools (Airflow, DBT, Presto, Hightouch).

Use diverse data sources to evaluate product performance, build automated ETL/data workflows, design dashboards and KPIs, own data product quality, and provide analytical insights to guide product and business decisions while establishing monitoring frameworks and best practices.

Design, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

Perform L3 network troubleshooting and RCA on production enterprise networks, review telemetry/logs/configs, label and annotate network behaviors for ML training, and help define schemas and data pipelines to support AI-driven infrastructure.