Top Data Jobs in Ottawa

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

Contributors record authentic first-person video of household tasks, hands-on work, and everyday activities using a phone mounted to a headstrap. They choose their own schedule, preferably recording at least 10 hours weekly, then upload footage through Perle’s app for review and payment. Contributors must be at least 18, reside in the United States, Canada, or Latin America, have a supported smartphone, and be comfortable wearing a headstrap.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

The Lead Engineer for BI will design data solutions, lead project teams, mentor, and drive BI strategy aligning with business needs.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

The Data Engineer will analyze and interpret data to drive insights, create dashboards, and enhance product performance, collaborating with cross-functional teams.

As a Data Analyst, you will analyze user behavior and product performance, creating reports and dashboards to aid decision-making and optimize user experience.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Lead a team in developing scalable data solutions, mentor engineers, manage expectations, and contribute to code. Focus on high-quality software practices.

Lead enterprise Data & AI transformation initiatives, managing the delivery of cloud-based analytics platforms while aligning business and technology objectives. Responsibilities include program governance, stakeholder management, and overseeing implementations of Microsoft Fabric.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

The Director of Data Strategy will develop and execute a data strategy, ensuring data quality and governance across the organization, fostering collaboration among various departments for improved analytics and business outcomes.

Own the AI and data product roadmap, prioritize and sequence development with engineering and founders, ship trustworthy AI experiences, drive adoption, define feature success metrics, evaluate outcomes, and manage the analytics foundation. The role requires technical fluency in AI, prior software engineering experience, production AI product delivery, strong product judgment, and comfort working in a fast-paced, remote startup environment.

Perform Sage Intacct data migrations, ETL, validation, reconciliation, cleanup, integrations, customizations, workflows, and automations. Support ERP implementation projects, troubleshoot data and web-service issues, create reports and templates, and train customers on data management tools and best practices. Collaborate with clients and internal teams to solve data challenges, estimate project requirements, and integrate Sage Intacct with CRM, construction management, payroll, and other systems. The role is remote with travel up to 20%.

Own the zero-to-one lifecycle for integrating structured financial data into AlphaSense. Translate investor research and capital-markets workflows into data requirements, architectures, and product solutions. Partner with engineering and platform teams across Web, Excel, and AI to deliver, test, launch, and enhance products. Conduct customer research, analyze competitors and industry trends, prioritize trade-offs, and align cross-functional stakeholders around product strategy and execution.

Lead predictive modeling and causal inference initiatives for clients, developing models from exploratory analysis through production deployment, monitoring, and retraining. Apply GLMs, econometric methods, uplift modeling, propensity methods, and deep-learning forecasting. Process large-scale data with SQL and Spark, build models in Python, improve production reliability, and communicate findings to technical and business stakeholders in a consulting environment.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Analyze go-to-market performance across marketing, sales, revenue operations, and finance. Build reporting connecting campaigns to pipeline and revenue, investigate funnel and attribution questions, support budget analysis and planning, improve data quality, and communicate insights to technical and non-technical stakeholders. Collaborate with AI and Data Engineering teams on marketing data agents, architecture, and source tables.

Take end-to-end ownership of backend features and SaaS services in a microservices architecture. Design, implement, deploy, and operate scalable, reliable Node.js services. Work with Redis Streams, MongoDB, Kubernetes, and ensure test coverage, performance tuning, and collaboration with cross-functional teams.

Own and drive the architecture and roadmap of ClickUp's data platform. Build scalable, reliable data pipelines and AI/ML infrastructure using AWS serverless, Snowflake, dbt, and Terraform. Lead cross-team technical initiatives, optimize cloud costs, establish engineering standards (observability, testing, CI/CD), mentor senior engineers, and influence org-wide architecture decisions.

Designs, builds, and maintains scalable batch and real-time data pipelines supporting an IoT safety ecosystem. The role manages ETL/ELT processes, data lakes, warehouses, lakehouses, orchestration, monitoring, data quality, and observability. It partners with product, engineering, analytics, and data science teams to deliver reliable data services, productionize models, and shape long-term data platform architecture using AWS and modern infrastructure practices.

Perform end-to-end data conversions for CityView implementations: map source-to-target data, develop reusable conversion scripts, troubleshoot issues, coordinate with customers and project teams, and deliver tested conversions to test and production environments while following CityView methodology and timelines.