Top Data Jobs in Ottawa

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.

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.

Sell Salesforce Data solutions to Canadian federal government agencies in Ottawa. Responsibilities include developing territory plans, building pipeline, managing public-sector accounts, identifying expansion opportunities, explaining data solutions to business and technical stakeholders, collaborating with partners and internal teams, addressing client issues, and reporting business progress. The role requires extensive enterprise technology sales experience, preferably with data platforms and Canadian public-sector clients.

Design and maintain scalable backend, full-stack, and AWS data infrastructure supporting millions of daily events and hundreds of integrations. Set technical direction for data pipelines, lead architecture and planning, troubleshoot production issues, collaborate across teams, manage work in Jira, research improvements, and mentor engineers. The role owns initiatives end to end while developing reliable, cost-efficient serverless systems using Node.js, TypeScript, React, and AWS services.

Define the architecture and technical direction of Coalition’s enterprise data platform. Build scalable Snowflake and dbt infrastructure, governed data models, batch and streaming pipelines, reusable data products, feature stores, semantic models, and AI data foundations. Establish standards for data quality, security, lineage, observability, and regulated workflows. Partner across engineering, product, underwriting, actuarial, security, and business teams while mentoring engineers and guiding cross-team architecture.

Owns Simbe’s product data management and Arena PLM administration for robotic hardware programs. Responsibilities include authoring and driving ECOs, MCOs, and deviations through approval; maintaining item masters, BOMs, approved vendor lists, part lifecycles, and documentation integrity; enforcing revision, numbering, and change-control standards; and coordinating implementation with Engineering, Operations, Supply Chain, suppliers, and contract manufacturers.

Own end-to-end analytical functions for growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and influence product, growth, finance, and operations decisions. The role requires strong independent data analysis, first-principles problem solving, clear communication, and ownership of ambiguous business challenges.

Own end-to-end data science for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence leadership decisions. The role requires independent analytical work, strong SQL or Python skills, first-principles problem solving, persuasive communication, and ownership of ambiguous problems. Candidates need 6+ years of experience in consulting, investment banking, or high-growth technology.

Own the analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, communicate insights, and drive decisions and outcomes with cross-functional stakeholders. The role requires strong analytical thinking, independent problem-solving, persuasive communication, and end-to-end ownership of ambiguous business challenges.

Own end-to-end analytical work for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, experiments, and analyses; surface insights; communicate recommendations; and influence product, growth, finance, and operations leaders to drive measurable outcomes.

Own end-to-end data science for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; communicate recommendations; and drive decisions and measurable outcomes with cross-functional stakeholders.

Own end-to-end data science for growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires strong SQL or Python skills, independent analytical problem-solving, clear communication, and ownership of ambiguous, high-impact initiatives.

Build and scale real-time and batch data pipelines, data platforms, and analytics-ready datasets using Kafka, Databricks, Snowflake, Python, and SQL. Design modern data models, ensure data quality and observability, develop AI-powered data experiences, and support business-critical reporting and analytics. Collaborate cross-functionally, improve platform performance, champion engineering best practices, and mentor teammates.

Manage CRM customer data migrations from onboarding through completion. Responsibilities include analyzing source Excel data, creating import rules, validating and reconciling migrated data, documenting mappings and transformation logic, resolving discrepancies, and coordinating with customers, engineers, sales, onboarding, and support teams. The role requires strong Excel and Google Sheets skills, analytical problem-solving, attention to detail, customer service, and effective communication.

Build and operate Block’s data platform, including warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop reliable Python services, developer tools, and Terraform infrastructure for petabyte-scale data. Partner with data practitioners and product teams, establish engineering standards, provide technical direction, and mentor engineers while ensuring security, reliability, observability, usability, and data governance.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Build and own Snout’s data foundation, including PostgreSQL and dbt warehouses, ingestion pipelines, dimensional models, data quality, documentation, and reliable rebuilds. Reconcile data from veterinary practice-management systems, support LLM/AI tooling, translate stakeholder needs into technical plans, and establish the foundation for a future data team and analyst.

Leads product marketing strategy, positioning, messaging, go-to-market execution, AI adoption, product launches, market expansion, and customer-driven roadmap input. Builds and manages a high-performing product marketing team, partners with executive, product, revenue, and marketing stakeholders, and drives product adoption, retention, category growth, and revenue across programmatic advertising and martech markets.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

Leads planning and roadmap execution for data orchestration capabilities across ingestion, transformation, routing, synchronization, monitoring, and delivery. Defines requirements for reusable pipelines, data contracts, schemas, lineage, observability, and AI-ready data flows. Partners with engineering, architecture, data, security, customer teams, and stakeholders to prioritize capabilities, improve reliability and adoption, reduce custom implementations, and establish measurable outcomes for data trust and onboarding efficiency.

Owns the strategy and roadmap for semantic insurance data products supporting AI, analytics, automation, and enterprise applications. Defines canonical concepts, relationships, metadata, data quality standards, APIs, knowledge graphs, and AI-ready consumption patterns. Partners with engineering, architecture, data, AI, UX, customer success, and insurance stakeholders to translate complex P&C insurance needs into product capabilities, prioritize use cases, establish requirements, drive adoption, and measure business impact.