Top Data Jobs in Ottawa

Lead enterprise-wide AI adoption by translating technical AI concepts for non-technical stakeholders, curating education and communications, partnering with change management and L&D, triaging requests, and building a team to drive measurable AI adoption across the organization.

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.

Own and operate the data plane: develop Envoy/WASM filters for deep packet inspection, deploy and manage EKS workloads with Helm/GitOps and CI/CD, integrate Redis sidecars, provide observability (Prometheus/Grafana/OpenTelemetry), ensure reliable audit log streaming, and author ADRs as the data plane evolves.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

Own and evolve Narvar's data pipelines, platforms, and data products on GCP. Design, build, and operate ETL/ELT workflows, data models, and embedded analytics using BigQuery and Airflow. Improve data quality, observability, lineage, and prepare datasets for LLM/AI use cases while collaborating cross-functionally and driving architectural decisions.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from ad platforms, order systems, and real-time events. Ensure reliability, observability, and maintainability across event-driven and batch architectures, implement authentication flows, optimize data workflows in a cloud-native environment, and collaborate with product, infrastructure, and data teams to onboard new sources.

Senior Data Scientist for Rovio's Beacon platform in Espoo. Develop predictive and statistical models for User Acquisition, handle long-term forecasting, uncertainty quantification, optimization, and rare-event behavior. Translate research into production, own model lifecycle from experimentation to deployment and monitoring, and collaborate closely with UA, game teams, finance, analysts, and engineers while contributing to a collaborative modelling culture.

Lead strategic architecture for front-office investment technology and data solutions, advising on platform selection and implementation (Aladdin, Charles River, Bloomberg, etc.), guiding data architecture, governance and quality, managing small-to-medium implementation teams, and ensuring delivery across portfolio management, trading, and reporting domains.

Lead client-facing Workiva implementation projects from discovery through go-live. Manage project delivery, design scalable Workiva solutions, run workshops, configure documents/spreadsheets/workflows, lead teams, support testing and training, and mentor consultants to ensure on-time, high-quality reporting and operational outcomes.

The role involves designing and implementing scalable data models using Data Vault techniques on Azure. Responsibilities include collaborating with stakeholders, optimizing data vault models, ensuring data security, and documenting data processes.

Design and optimize SQL Server solutions, manage data, automate processes with PowerShell, and integrate with external systems to enhance functionality.

As a Data Analyst, you will analyze user behavior, create interactive dashboards, and collaborate with teams to provide actionable insights for product improvement.

Analyze user behavior and product performance, create reports and dashboards, and provide data-driven insights to teams for decision-making.

As a Backend Engineer on the Data team, you will design and maintain data pipelines and services, ensuring data quality and scalability while collaborating with cross-functional teams to meet data needs.

The role involves designing, building, and deploying machine learning models, collaborating with teams to address business problems, and mentoring other data scientists.

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

Lead a distributed team of data scientists and engineers, focusing on data infrastructure and ML systems while collaborating with product and marketing teams.

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.

Use customer, digital, and transportation data to build targeting, propensity, pricing, loyalty, and churn models; run experiments (A/B), optimize promotions and pricing, present insights to stakeholders, manage data structures in Databricks/AWS, and lead project work with business partners to drive data-driven decisions.

The Data Conversion Engineer will manage data migration processes from legacy systems to a modern platform, developing ETL processes and ensuring data quality and reliability.

Design, build, and maintain core Power Query components for data connectivity and transformation. Develop high-performance, reliable systems for diverse data sources, improve scalability and query execution, collaborate with partner teams (Power BI, Fabric, Excel), and diagnose complex production issues across clients, services, and data sources.

Design, build, and operate a cloud-native data and ML platform handling billions of events. Own end-to-end pipelines, feature stores, model training/serving, observability, and data product SLAs. Apply distributed systems, MLOps, and LLM/agentic systems to ensure reliable, low-latency access to features and production models with business-focused impact.

Own analysis and algorithmic solutions for ads delivery; train, deploy, and scale ML/optimization models into production; build logging, monitoring, and lineage; improve data pipelines; mentor data scientists; use agentic AI tools daily; collaborate with engineers to integrate models into ads systems and handle on-call production incidents.

Own analytics enablement by translating stakeholder questions into trusted, reusable metrics and semantic models. Build and maintain the metrics/semantic layer, validation, documentation, AI-accessible datasets, and pipelines to ingest new sources. Enable self-serve analytics and agentic LLM querying (Claude) while partnering with product, GTM, and executives.

Lead design and implementation of scalable, secure Forma Data cloud services. Act as technical lead across full software lifecycle, write and operate cloud services, mentor engineers, solve complex distributed-system problems, and collaborate globally to integrate SaaS products with Autodesk tools.