Top Data Jobs in Ottawa

Configure and integrate Total Learning Architecture components (LMS, LOR, LRS, Synthetic Training Hub) to enable xAPI data pipelines, validate end-to-end data flows, implement learning analytics and Power BI reporting, support UAT, and provide SME guidance for cloud-native training content and simulation integrations.

As a Sr. Data Engineer, you'll design and manage data pipelines, enhance data quality, and leverage AI to streamline operations, driving the success of our AI growth platform for real estate.

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.

Lead vision, roadmap, and hands-on delivery of a secure AI, GenAI, and data platform in AWS. Implement Amazon Bedrock and SageMaker powered GenAI and MLOps capabilities, establish secure data foundations, define guardrails/compliance automation, own platform reliability and onboarding, and drive cross-functional adoption and governance for regulated environments.

Collect and record pedestrian counts at designated intersections during AM and PM shifts in September/October 2026. Follow protocols, use a smartphone for data entry, work outdoors in varied weather, maintain safety and professionalism, and report to the Program Manager for School Zone Safety.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.

This role involves outbound prospecting, conducting cold calls, emails, and LinkedIn outreach to qualify opportunities and set meetings in a remote capacity.

CommBank is seeking Indigenous job seekers for various roles across its sectors, offering traineeships, internships, and direct employment opportunities with support from an Indigenous Careers team.

Review and analyze news content from patient advocacy groups, extract insights, and input data into Zebricks to support AI/ML processes. Collaborate with the team on data projects, shape data best practices, and perform web research and spreadsheet-based data work.

Lead enterprise data, analytics, and AI transformation engagements as a strategic advisor and architect. Design cloud data platforms, warehouses/lakehouses, governance, BI/semantic models, and integration strategies. Provide delivery oversight, mentor teams, conduct architecture reviews, and support pre-sales and thought leadership to drive measurable business outcomes.

Perform accurate, timely data entry and document typing/proofreading, organize and categorize records, collaborate with remote team members, and follow company data management policies.

Perform remote data entry tasks: enter, update, verify, and correct information in company databases while maintaining accuracy, confidentiality, and meeting deadlines. Follow instructions and work independently.

Build and maintain real-time streaming data pipelines and feature stores to power low-latency model inference. Collaborate with ML and AI infra teams on data contracts, observability, and SLAs; drive batch-to-real-time migrations and evaluate emerging streaming/feature store technologies.

Design, build, and own streaming data pipelines and feature stores to enable low-latency inference and real-time model serving. Partner with ML and infra teams to define data contracts, ensure data quality, observability, and SLAs, and move batch pipelines toward real-time production. Evaluate streaming and feature store technologies and contribute to inference pipeline tooling.

Lead the design and development of a data platform, integrating data sources, driving architecture migration, and ensuring robust data governance and API development.

As a Senior Data Analyst, you will support Finance and Payments teams by building SQL/dbt models, creating Looker dashboards, and providing actionable financial insights.

The Engineering Manager will lead cross-functional teams of engineers, focusing on building high-performing environments, managing technical delivery, fostering team growth, and ensuring data-driven strategies.

Lead data-driven underwriting improvements by analyzing claims, risk signals, and underwriting data; build statistical and ML models for cyber risk assessment, pricing, and automation; produce dashboards and reports; collaborate with actuarial, product, and engineering teams; mentor teammates and lead cross-functional initiatives to optimize underwriting and risk selection.

Design, build, and maintain scalable Databricks-based ETL/ELT pipelines and data models optimized for AI/ML. Manage orchestration, data quality, governance, and CI/CD (ADO → GitHub) while collaborating with cross-functional teams in Agile delivery.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

Manage a team of cloud engineers and architects, oversee data delivery, lead technical discussions, and mentor team members while ensuring technical accountability on projects.

Lead and develop a team to govern and validate clinical data builds, vendor deliverables, and data integrations. Implement and maintain CDASH/SDTM/ADaM standards, validation libraries, and submission-ready processes. Oversee data ingestion into the Clinical Data Warehouse, drive automation (SAS, Python, AI), maintain SOPs/QMS, and partner with Biostatistics, Data Management, Standards, and CROs to ensure high-quality, analysis-ready datasets.

Lead optimization and scaling of Snowflake architecture, build resilient ELT/ETL and MLOps pipelines, implement data observability, automate workflows with AI-assisted tools, and design enterprise semantic models to support analytics and commercial data products.

Lead and manage client data and digital strategy projects end-to-end: plan and run projects, produce C-level deliverables, coach and evaluate teams, perform advanced data analysis, define client needs, pitch solutions, and develop business proposals to grow accounts.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.