Top Data Jobs in Ottawa

Build and ship production AI systems across retrieval, knowledge graphs, inference, agentic workflows, and data platforms. Develop customer-context retrieval, scored signals, workflow automation, evaluation, and observability capabilities. Work hands-on with Python, SQL, dbt, lakehouse data, cloud infrastructure, model selection, and inference-cost optimization. Establish reusable engineering patterns and mentor teams through high-quality code and system design.

Own the strategy, roadmap, and delivery of Coalition’s scanning and cyber-risk data products. Partner with Engineering, Data, Security, Underwriting, Actuarial, Design, and customer teams to improve asset discovery, data quality, accuracy, reliability, scalability, and usability. Define metrics, prioritize initiatives, translate technical challenges into product requirements, guide discovery through launch, and develop APIs and experiences that help stakeholders understand and act on cyber-risk intelligence.

Leads advanced data analytics for Tribal healthcare initiatives, including data resource inventories, quality assessment, linkage analysis, predictive and prescriptive modeling, reporting, dashboards, and large-scale analytics projects. Establishes data quality frameworks, supports federal compliance, coordinates cross-functional initiatives, and mentors junior analysts. Uses Python, R, SQL, statistical methods, machine learning, and data modeling to produce actionable insights and maintain data integrity.

Own and evolve WorkOS’s internal data platform, including ingestion, orchestration, Snowflake, dbt models, data governance, reverse ETL, semantic views, and AI-enabled data workflows. Ensure pipeline reliability, freshness, security, and scalability while partnering with Product, Finance, RevOps, GTM, Engineering, and Security. Build monitoring, runbooks, CI/CD gates, access controls, masking policies, and infrastructure automation across AWS and Kubernetes.

Own end-to-end financial data analysis, including SQL and dbt data modeling, Looker dashboard development, data quality validation, reconciliation, and stakeholder-facing insights. Partner with Finance and Payments to support reporting, planning, revenue analysis, cost insights, and transaction-level analytics. Translate ambiguous business needs into reliable technical solutions while improving documentation, QA, modeling, and data architecture practices.

Business-focused consultant connecting divisions with enterprise data, analytics, and AI functions. Facilitates discovery workshops, identifies technology opportunities, translates business challenges into AI and data use cases, and develops decision-ready business cases covering benefits, costs, risks, dependencies, and value realization. Partners with business, finance, technology, and delivery teams to guide opportunities through prioritization, delivery, adoption, and measurable outcomes.

Build production AI harness systems for Kinaxis’s Databricks-based enterprise Data Fabric. Responsibilities include developing agent execution frameworks, integrating LLMs with governed data, implementing tool calling and workflow controls, enforcing multi-tenant isolation, and delivering APIs, SDKs, libraries, templates, and operational runbooks. The role requires distributed-systems engineering, cloud data-platform experience, secure multi-tenant design, and practical expertise in agent orchestration, retrieval, evaluation, guardrails, metadata, lineage, and governance.

Own growth marketing data science for a key domain, developing optimization algorithms, attribution and incrementality models, experimentation strategies, analytics pipelines, dashboards, and strategic insights. Partner with marketing, product, engineering, data engineers, and ad platforms to improve customer acquisition, campaign performance, and marketing ROI. Serve as the end-to-end data domain owner and translate complex analyses into business decisions.

Lead the architecture and hands-on engineering of Cloudbeds’ Snowflake and dbt data platform. Own data modeling, warehouse design, ingestion, orchestration, DataOps, CI/CD, governance, observability, performance, cost optimization, and AI/ML readiness. Mentor analytical engineers, evaluate emerging tools, establish data quality and security standards, and collaborate with engineering, infrastructure, data science, and business stakeholders in a fully remote environment.

Leads complex data science and analytics initiatives, develops and validates predictive models, evaluates diverse data sources, and translates findings into actionable business insights. Determines technical approaches, supports risk mitigation and decision-making, and provides technical leadership and mentorship to analytics professionals. Collaborates with stakeholders while promoting quality, consistency, and data-driven solutions.

Design, build, and maintain scalable data ingestion pipelines, databases and data lakes for credit and lending datasets. Ensure accurate data mappings, monitoring and alerting, translate stakeholder requirements into analytical data flows, and integrate APIs to deliver reliable, high-quality data products.

Drive strategic federal sales growth across DISA 4th Estate and Intelligence Community accounts. Responsibilities include pipeline development, account planning, opportunity and win strategy, stakeholder relationship development, acquisition navigation, RFI and solicitation support, CRM management, forecasting, and translating technology solutions into mission outcomes. The role requires expertise in long-cycle federal sales, procurement processes, secure environments, and technology solutions.

Lead CBC/Radio-Canada’s enterprise data governance program, including policies, data classification, catalogs, metadata, quality, lineage, compliance, and AI readiness. The role oversees governance councils, data stewards, executive reporting, literacy initiatives, and a small governance team. Responsibilities include partnering with Legal, InfoSec, engineering, analytics, and business stakeholders to establish consistent data management practices across a national, matrixed organization.

Drives adoption of the enterprise data governance framework across business and technology domains. The role deploys governance tools and policies, coordinates data teams and working groups, tracks roadmaps and milestones, supports data quality initiatives, maintains documentation, and develops dashboards and executive briefings. It also facilitates stakeholder education, workshops, communications, and action-item tracking while partnering with engineering and BI teams.

Sells new business and manages and expands client portfolios for CoStar’s commercial real estate data and analytics products. Responsibilities include prospecting, product demonstrations, consultative selling, closing, onboarding, training, renewals, account management, client meetings, and industry event representation. The role requires exceeding sales targets, building client relationships, and developing expertise in commercial real estate markets and CoStar products.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, LTV, and next-best-action decisioning. Design reliable signal contracts covering freshness, provenance, confidence, eligibility, and calibration. Lead feature pipelines, model serving, experimentation, monitoring, and feedback loops while evaluating fairness, risk, compliance, trust, and long-term customer impact. Collaborate across product, growth, data, platform, modeling, risk, and compliance teams.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, lifecycle intelligence, and next-best-action decisioning. Design reliable signal contracts with freshness, provenance, confidence, and calibration guarantees. Lead experimentation, monitoring, feedback loops, and impact evaluation focused on fairness, trust, risk, compliance, and long-term engagement. Partner across product, growth, data, platform, modeling, risk, and compliance teams.

Own the vision, strategy, roadmap, development, commercialization, and lifecycle of commercial data products. Identify customer and market opportunities, translate needs into product requirements, and collaborate with data engineering, data science, analytics, software, sales, and marketing teams. Lead discovery, launches, monetization, adoption, optimization, and measurement of business outcomes across revenue, operations, customer experience, and decision-making.

Evaluate AI model outputs, audit data and model behavior, identify edge cases and failure modes, apply and improve evaluation guidelines, communicate performance trends, participate in calibration discussions, and document actionable findings. The role requires native-level Tamil, strong English and writing skills, critical judgment, attention to detail, and familiarity with GenAI safety considerations. This is a full-time, one-year, 100% onsite contract position.

Evaluate AI model outputs, conduct audit-based reviews, identify patterns and failure modes, apply and improve evaluation guidelines, and document actionable findings. The role requires native-level Marathi, strong English, structured writing, GenAI safety knowledge, critical thinking, and comfort making judgment calls in ambiguous situations. Associates collaborate with leads and stakeholders, participate in calibrations, and help refine quality standards. This is a full-time, one-year, 100% onsite contract role in specified U.S. cities.

Leads integration of two major financial data product launches into the AlphaSense platform. Defines zero-to-one product lifecycles, user stories, milestones, roadmaps, and PRDs; translates investment research workflows into data architectures; manages resources and delivery across teams; mentors product managers; validates solutions with customers and engineering; and drives competitive intelligence, prioritization, and cross-functional alignment.

Design, build, and support production data feeds and integration pipelines using Python, SQL Server, Snowflake, REST APIs, SFTP, Docker, and AWS ECS. Develop incremental-loading workflows, apply Data Vault modeling, troubleshoot end-to-end data pipelines, and implement validation, monitoring, logging, error handling, and retries. Collaborate with technical and business stakeholders while maintaining pipeline and operational documentation.

Lead the architecture and implementation of a Microsoft Fabric data platform, including migration from Azure Synapse, secure networking, near-real-time ingestion, data protection, and Medallion architecture. Design ingestion from Oracle and SQL Server systems, guide capacity and cost strategy, validate GCC High capabilities, mentor data engineers, review technical work, resolve complex challenges, and communicate architecture decisions to client stakeholders.

Annotate robot episodes, videos, images, and sensor data for robotics AI models. Label objects, actions, task steps, and outcomes; write behavioral descriptions; identify ambiguous cases; perform annotation quality checks; meet accuracy and throughput goals; and report tool or workflow issues to engineering. The role requires high attention to detail, strong written communication, sound judgment, and comfort working under deadlines and ambiguity.

Manages Clinical Data Science staff, client relationships, project delivery, budgets, quality, utilization, training, and regulatory readiness across clinical studies. Oversees clinical data science activities from project launch through closeout, supports audits and CAPAs, monitors data quality and risk, mentors team members, contributes to business development, and helps develop tools, SOPs, and processes for clinical data management.