Top Data Jobs in Ottawa

Lead full-cycle enterprise sales for data and intelligence consulting: originate pipeline, run discovery, manage complex multi-stakeholder deals, create SOWs with delivery teams, co-sell with partners, and meet revenue targets while leveraging AI tools.

Lead product execution for retail platforms, integrations, and data foundations. Establish data governance, define integration patterns and data contracts, improve fulfillment/OMS capabilities, evaluate vendors, and enable analytics and AI-driven automation to increase operational efficiency.

Perform product and player-behavior analysis for Marvel Strike Force using SQL/Python and reporting tools. Build recurring KPI reports, design/validate analytics tracking and experiments, partner with cross-functional teams, and use AI-enabled tools to accelerate workflows while ensuring data quality, privacy, and clear executive-ready insights.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Lead and execute end-to-end Salesforce data migration projects: define strategy, design and validate data models, build ETL pipelines, resolve data quality issues, perform reconciliation and validation, document mappings, and coordinate cross-functional teams to ensure compliant, accurate migrations on schedule.

As a Data Engineer, you'll design, build, and maintain data pipelines, ensure data quality, and collaborate with stakeholders to deliver data solutions.

Lead and grow a small data team while remaining hands-on in data engineering, analytics engineering, and infrastructure. Own data strategy, warehouse architecture, pipelines, modeling, and self-serve analytics. Partner cross-functionally to deliver trusted metrics, experimentation, and applied ML capabilities (search, recommendations, personalization). Drive adoption of data quality, documentation, self-service, and modern data practices.

Label and review 2D images and 3D sensor (LiDAR) data using annotation tools to create bounding boxes, cuboids, and other shapes. Ensure annotations follow guidelines, correct or reject pre-labeled data, provide notes, learn internal tools, and collaborate to improve data quality for autonomous vehicle AI.

Build and own a versioned, documented gold data layer from lakehouse silver tables for AI research. Transform, validate, and productize multi-modal datasets and pipelines (Databricks/PySpark) to support model development, evaluation, and production ML/LLM workflows while ensuring data quality, provenance, and regulatory controls.

The Data Migration Specialist will manage end-to-end data migrations, ensuring data quality and effective communication with clients and internal teams while resolving challenges.

The Data Product Manager defines the reporting roadmap, manages KPI alignment, collaborates cross-functionally, ensures data quality, and leads continuous improvement in analytics processes.

Evaluate and label model-generated and human-written software engineering outputs for coding, debugging, and codebase-related tasks. Assess agent trajectories, prompt models for complex coding tasks, proofread and improve responses, and report quality and performance trends. Part-time contractor role contributing to model development.

The Forward Deployed Marketing Data Scientist will work with AI customers and engineering teams to optimize AI-driven marketing campaigns through data analysis, diagnostics, and communication of insights to stakeholders.

Design and optimize data pipelines, lead machine learning feature integration, mentor junior engineers, and enforce data governance.

Design and build operational data systems, including pipelines, storage layers, and APIs for near real-time enforcement and insights, balancing streaming and batch paradigms.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

Lead end-to-end client ML engagements: scope problems, design, build, and deploy production ML solutions across cloud and containerized stacks. Lead and mentor small teams, manage client relationships, evaluate emerging tools, and ensure models are production-ready and explainable to technical and non-technical stakeholders.

The Account Manager focuses on Commercial & Industrial sales, driving business growth by developing relationships, achieving sales targets, and delivering value-based solutions in renewable energy and data sectors.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

As a Data Analyst at Stripe, you'll build data products, metrics, and dashboards, analyze large datasets, and communicate insights to drive business decisions.

Lead and support analytics lifecycle activities: manage analytic data platforms, govern data access, design and implement reporting/BI, apply advanced quantitative modeling, deliver actionable business insights, contribute to policies, work independently on complex projects and mentor junior colleagues.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

The Senior Data Engineer will lead the design and development of scalable data infrastructure for analytics and AI capabilities, ensuring compliant data processing systems and improving the data platform.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, collaborate with teams, and uphold data governance at Mozilla.

The Senior Data Engineer will create and manage data pipelines, ensuring data quality, collaborating with teams for data-driven decisions, and evolving the data platform.