Top Data Jobs in Ottawa

Design business data models and data architectures, mentor data teams, translate business requirements into technical specifications, and set standards for AI-augmented development practices.

The Data Governance Intern will assist in developing enterprise data catalogs, documenting data elements, and supporting data quality efforts using SQL and Python.

Lead and scale the Growth engineering organization at MaintainX, focusing on technical strategy, product-led growth, and enhancing cross-functional initiatives.

As a Senior Product Manager, you'll drive product strategy for Wrapbook's tech enablement team, collaborating cross-functionally and managing product roadmaps and execution for critical features.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

The AI Data Expert will review and evaluate AI-generated outputs and textual content, ensuring cultural relevance and quality. Responsibilities include content analysis, assessing multimedia materials, and providing structured annotations while adhering to detailed guidelines. Native fluency in French and strong English skills are essential, with previous experience in AI evaluation preferred.

Evaluate and review AI outputs, generate or assess content, and ensure cultural relevance and accuracy in various media for AI projects.

As a Senior Data Engineer, you will build scalable data pipelines, manage cloud infrastructure, and support analytics and data science teams, leveraging various technologies to deliver impactful solutions for clients.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Lead and scale a product-focused Data Science team to drive acquisition, engagement, retention, and member health outcomes. Set DS strategy, measurement frameworks, operating model, and prioritize high-impact analytics. Partner cross-functionally, ensure rigorous, actionable analyses, apply experimentation, causal inference, segmentation, forecasting and personalization, and collaborate with data engineering to improve data foundations.

Lead Data Acquisition Team, drive AI-augmented development, establish specification-driven methodology, oversee data pipeline architecture and ensure operational excellence.

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.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

Lead Harbor's Data & AI consulting service line for law firms: own P&L and financial performance, develop and productize offerings, oversee delivery and talent development, drive business development and market thought leadership, and ensure measurable client value.

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 governance, review, and validation of clinical data deliverables ensuring CDISC/SDTM compliance and submission readiness. Oversee EDC/eCRF design, data quality control frameworks, vendor deliverable review, reporting/visualization, and integration of external data sources. Support scalable data platforms, automation, and AI-enabled capabilities while partnering with Data Management, Statistics, and vendors to ensure data traceability and regulatory alignment.

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

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.

Proactively explore RevenueCat's data to identify product opportunities, translate ambiguous problems into analyses and production-grade predictive/descriptive models, partner with Product and Engineering to ship data-powered features (LTV prediction, experimentation, benchmarking), define statistical approaches, iterate on models in production, and communicate insights to technical and non-technical audiences.

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.

The Senior Data Architect will optimize data architecture strategies, support data lifecycle activities, manage database systems, and ensure data integrity while collaborating with business partners.

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.

Lead end-to-end AI product development: define KPIs, design and train foundation/transformer models, run rigorous experiments (A/B, causal inference), build production training pipelines and evaluation harnesses, analyze feedback, and mentor teammates to translate models into measurable product impact.

Analyze and document business and system requirements for an Intelligence Mission Data project; facilitate workshops and use-case development; produce system specifications and traceability; perform technical options analysis and solution evaluations; plan organizational impact and integration; participate in testing; and prepare briefings, reports, and meeting artifacts.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.