Top Data Jobs in Ottawa

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.

Analyze, validate, and standardize community health data; identify trends, outcomes, quality issues, and impact indicators; improve collection and reporting practices; and translate findings into accessible reports, visualizations, communications, advocacy materials, and funding applications. The role collaborates with multiple member organizations, supports program evaluation and impact measurement, protects confidential information, and contributes to logic models, work plans, outcome measures, policies, and data practices.

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.

Lead marketing analytics and data strategy for B2B SaaS Marketing. Design measurement frameworks, own attribution, funnel and lifecycle analysis, forecasting, and marketing investment recommendations. Partner with senior marketing leaders and cross-functional teams to build data foundations, enable AI-assisted analytics, and mentor analysts to raise analytical standards.

Explore large-scale AI evaluation datasets, identify patterns, biases, and causal relationships, and design experiments to understand model behavior. Build reproducible analysis pipelines with Python, Pandas, NumPy, and Spark; develop statistical and causal inference frameworks; partner with ML researchers and engineers; and communicate findings to technical and non-technical stakeholders.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

Lead enterprise data architecture and transformation initiatives for financial-services clients. Responsibilities include defining target-state architectures, operating models, roadmaps, integration patterns, data governance, platform strategies, and architectural standards. The role evaluates vendors and build-versus-buy decisions, leads workshops and delivery teams, communicates with executives, manages complex projects, develops internal intellectual property, and mentors consultants. Strong expertise in MDM, data modeling, integration, cloud data platforms, governance, quality, security, and asset and wealth management data is required.

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

Own Orum’s data platform architecture, roadmap, reliability, and scalability. Build batch and real-time ETL/ELT pipelines using PostgreSQL, event streams, ClickHouse, BigQuery, and dbt. Administer Looker and develop LookML models, dashboards, and a trusted semantic layer. Establish data quality, governance, lineage, observability, and metric standards while partnering with Product, Finance, GTM, and Operations on analytics, AI, and business intelligence initiatives.