Top Data Jobs in Ottawa

The MDM Data Analyst will translate business needs into data requirements, document governance rules, and ensure high-quality master data management across enterprise systems.

The Senior Data Platform Engineer will design and operate a unified data platform, ensuring reliable data flows and collaborating across teams to shape data strategy and architecture.

The Data Analyst, Growth will analyze marketing data to deliver actionable insights, design dashboards, automate reporting, and support cross-functional projects to improve client acquisition and retention.

Lead Kraken's Data Platform team focused on real-time infrastructure for data systems, managing team dynamics, architecture design, and promoting AI automation.

Lead RWD analysis strategy and execution: develop technical specifications and statistical programs, perform complex observational analyses (propensity scoring, ML), validate cohorts/variables, ensure QC, collaborate cross-functionally, and communicate results to non-technical stakeholders.

The Data Systems Operations Lead will manage operations for Pyth's Price Feeds, ensuring flawless service through automation, incident management, and strategic improvements.

Design and deliver enterprise-scale EDW and BI solutions, ensuring performance and scalability, while mentoring teams and engaging stakeholders.

The role involves enhancing the model evaluation platform by working on backend, infrastructure, frontend, and performance tasks. Interns will collaborate with a senior engineer to build and deploy new features using cutting-edge AI technologies.

Lead and advise on data architecture and datastore designs, ensuring scalability and reliability, while managing cross-application projects and influencing technical decisions.

The VP of Data & AI Engineering leads Duck Creek's enterprise data and AI strategy, overseeing global teams, implementing scalable platforms, and ensuring data governance and responsible AI practices.

The Staff Data Engineer will architect scalable data systems, enforce engineering standards, mentor teams, and drive real-time analytics at Life360.

Lead design and implement a scalable Medallion lakehouse on GCS and Databricks. Build and govern ingestion and transformation pipelines (Astro/Airflow, PySpark, Delta Live Tables), apply domain-driven data modeling, manage Unity Catalog access and lineage, collaborate with analytics and vendors, and proactively surface risks with clear documentation.

The Data Reliability Engineer will enhance the resilience and scalability of data infrastructure, focusing on automation and reliability. Responsibilities include managing data pipelines, operating Kubernetes clusters, and defining observability standards.

As a Data Annotation Specialist, you will label, audit, and optimize data for AI models in Chinese while ensuring high accuracy and quality. You will perform repetitive tasks and collaborate with teams, providing feedback and recommendations for data improvement.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

Lead the data and ML product vision: define roadmap, prototype models on noisy behavioral datasets, translate signals into user-facing features, partner with engineering to productionize ML, and generate insights to inform product roadmaps.

Embed with a core business unit to define problems, build metrics, run analyses and experiments, surface insights, and drive data-backed recommendations end-to-end to improve product, growth, AI/automation, or partnerships.

Embedded in a core business area, own end-to-end analytics: define problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-informed recommendations to improve product, growth, AI, and partnership outcomes.

Embedded on a core business team, own end-to-end analytics: define problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-informed decisions with stakeholders to improve product, growth, AI/automation, or partnerships.

Own the analytics function embedded in a business unit: define problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end to impact growth, product, AI/automation, or partnerships.

Embedded on a core business team, you will define analytical problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed recommendations end-to-end to improve product, growth, AI, or partnerships.

Embedded on a core business team, the Data Scientist will define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embed with a core business unit to define analytical problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end to impact growth, product, AI, or partnerships.

Lead embedded data science for a core business area (growth, product, AI/automation, or partnerships). Define problems, build metrics and analyses, run experiments, surface insights, make recommendations, and drive execution cross-functionally to improve key business metrics.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.