Top Data Jobs in Ottawa

Build and operate scalable data pipelines supporting batch and streaming workloads, AI and ML systems, analytics, and sports intelligence products. Responsibilities include ETL/ELT development, data modeling, orchestration, retrieval pipelines, data quality, lineage, monitoring, infrastructure optimization, and collaboration with ML, product, and analytics teams.

Staff Data Scientist responsible for owning ambiguous, high-impact product and business problems; designing experiments; analyzing product data; developing analytical tools and frameworks; partnering with product, engineering, design, and leadership; and mentoring data scientists. The role requires advanced statistical expertise, strong product judgment, production programming experience, and the ability to translate complex analyses into strategic recommendations.

Lead executive interviews, stakeholder workshops, and current-state assessments to identify operational gaps and opportunities. Develop business cases, operating models, governance, KPIs, roadmaps, and practical AI-enabled solutions. Advise on AI strategy, innovation, commercialization, customer experience, and change management. Support transition of recommendations to delivery teams and occasionally participate in business development.

Develop and deploy statistical and machine learning models for credit risk, fraud, collections, and marketing. Responsibilities include data exploration, model development, production monitoring, performance analysis, governance, stakeholder collaboration, and communicating insights to leadership. The role requires applying advanced statistics and machine learning to improve consumer finance strategies while maintaining documentation, quality assurance, and version-control standards.

Design, build, and operate production AI systems and marketing data infrastructure. Develop retrieval pipelines, agent orchestration, CDP integrations, ETL/ELT pipelines, and analytics. Automate workflows with AI, ensure data quality and reliability, partner with stakeholders, ship Python and SQL code, mentor engineers, and drive requirements to production.

Leads clinical data management activities from study start-up through database lock for complex clinical research projects. Oversees data quality, documentation, project teams, and multiple studies; leads and mentors clinical data managers; ensures compliance with SOPs, sponsor requirements, ICH GCP, and applicable regulations. Provides technical leadership, training, consulting, project planning, and data management expertise across internal and external teams.

Lead the development, validation, and maintenance of clinical data programming solutions for EDC/CDMS systems, vendor data, analytics, reports, integrations, and data transfers. Provide technical leadership across studies, serve as a programming subject matter expert, mentor programmers, support study teams, and drive automation and process improvements. Collaborate with data managers, biostatisticians, and project managers to ensure high-quality clinical trial data management solutions.

Lead client-facing Workiva implementation projects from discovery through go-live. Manage project delivery, design scalable Workiva solutions, run workshops, configure documents/spreadsheets/workflows, lead teams, support testing and training, and mentor consultants to ensure on-time, high-quality reporting and operational outcomes.

Develops, validates, and maintains clinical data programming solutions for CDMS and clinical trials, including eCRFs, edit checks, data validation outputs, reports, extracts, transfers, and vendor data programs. Collaborates with cross-functional clinical data teams, supports study setup and maintenance, mentors junior programmers, creates training materials, and improves technical systems and processes.

Design and build durable, distributed data-streaming infrastructure that decouples process data from Camunda’s live execution engine. Develop customer-facing integrations such as Kafka connectivity, support analytics data consumption at scale, and make architecture decisions around consistency, durability, and storage. Participate in production support and on-call rotations while collaborating with Product, Data Layer, Distributed Systems, QA, SRE, and Support teams. Lead ambiguous, cross-functional engineering initiatives from design through delivery.

Annotate and manage training/test datasets, run model training, evaluate model performance, perform manual QA and error analysis, and refine annotation guidelines for NLP/ML projects.

Leads AI data annotation operations, managing workflows, resources, productivity, quality assurance, and project timelines. Coaches and develops annotation teams, supports recruitment, and collaborates with AI engineers, trainers, and product teams. Establishes annotation guidelines, conducts audits, resolves quality issues, and drives process improvements, automation, tool adoption, and operational excellence across AI data initiatives.

Labels, categorizes, validates, and quality-checks structured and unstructured data used to train AI and machine learning models. Maintains dataset accuracy, consistency, documentation, and version control while following detailed annotation guidelines. Collaborates with AI engineers, data scientists, and quality teams, identifies errors, provides process feedback, and supports continuous improvement of annotation workflows.

Leads a data engineering team responsible for large-scale streaming and batch ingestion pipelines, data transformations, and semantic data domains. Oversees architecture, implementation, reliability, observability, performance, and data quality improvements while mentoring engineers and driving delivery. Collaborates with product, engineering, support, and business teams, and promotes AI-assisted development and modern data architecture.

Build and ship end-to-end ML/AI systems (traditional ML, NLP, LLMs/AI agents) on transaction, merchant, and location data. Prototype, productionize, and monitor models, collaborate with engineering and product, and (for senior hires) shape roadmap and mentor teammates.

Own the technical sales motion for NVIDIA-focused enterprise AI infrastructure deals. Lead discovery, architecture, proof-of-concept design and execution, technical closes, partner and field SE enablement, troubleshooting, escalation, customer workshops, and product feedback. The role requires expertise in NVIDIA systems, storage, data platforms, Linux, parallel file environments, GPU clusters, and AI pipelines, with Bay Area availability for on-site partner or customer sessions.

Designs and improves large-scale data processing systems and GCP workflows using Dataflow, BigQuery, Pub/Sub, GKE, and Airflow. Evaluates technologies, establishes engineering standards, leads cross-functional data projects, develops data abstractions with Data Science, mentors engineers, and supports evolving data products.

Leads North American indirect tax requirements and global tax data governance for an SAP S/4HANA transformation. Oversees U.S. and Canadian tax processes, tax determination, reporting, reconciliations, data standards, tax technology integrations, testing, deployment, audit readiness, and compliance. Partners across Tax, Finance, IT, Master Data, Analytics, Procurement, Supply Chain, and Shared Services to improve tax data quality and establish scalable global operating models.

Analyze large datasets to produce dashboards, metrics, and insights supporting product, care, and business decisions. Build BI infrastructure, run A/B and multivariate tests, perform ad-hoc analyses and visualizations, and collaborate with stakeholders and data scientists to inform strategy and operations.

Reviews and evaluates clinical trial data within oncology studies, supporting data quality, consistency, and drug development objectives. Collaborates with clinical solutions and study teams to identify issues, apply therapeutic expertise, and help deliver reliable outcomes for life sciences customers.

Lead product marketing for Procore AI & Data products: own positioning, messaging, launches, competitive positioning, sales enablement, and cross-functional GTM programs. Collaborate with Product, Demand Gen, Sales, and global Marketing to create customer-facing content and drive adoption.

Supports the analysis and definition of an Intelligence Mission Data project for a defence client. Gathers and documents requirements, facilitates use-case workshops, develops system specifications and traceability, evaluates technical alternatives, assesses organizational impacts, and supports solution testing and integration. The role also prepares briefings, meeting documentation, action reports, and progress updates while collaborating with users, customers, stakeholders, and project staff.

Leads the enterprise data and integration capability by developing strategy, architecture, governance, standards, roadmaps, and operating models. Establishes scalable APIs, data pipelines, event-driven integrations, metadata, lineage, master data, and quality practices. Provides strategic leadership for data platforms, analytics, AI readiness, and modernization; evaluates technologies and vendors; leads a Data Engineering team; and partners with business, technology, cybersecurity, infrastructure, and external stakeholders to improve enterprise data delivery and governance.

Leads the enterprise data and integration function by developing strategy, architecture, governance, standards, roadmaps, and scalable data capabilities. The role oversees integration architecture, APIs, data platforms, pipelines, metadata, data quality, analytics, AI readiness, and modernization. It also leads a Data Engineering team, evaluates technologies and vendors, establishes governance, reduces technical debt, and partners with business, cybersecurity, infrastructure, applications, and architecture leaders.

Designs and deploys data integration, data management, reporting functionality, and data models for insurance-sector transformation projects. The role analyzes client needs, configures SAP solutions, applies data modeling expertise, and collaborates with software development and sales teams. Candidates need experience with IT transformation, insurance data processes, SAP FDS or SAP BW solutions, SAP HANA technologies, and technical mapping. The position is Canada-based with 50% travel and occasional on-site work in Calgary or Toronto.