Top Data Jobs in Ottawa

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.

Lead labeling quality and methodology for ML at Coalition: design annotation tasks, define quality frameworks (IAA, gold standards), manage Label Studio and vendor BPOs, partner with ML/data teams, and track operational metrics to improve accuracy and throughput.

Lead data management for clinical trials including database setup, eCRF specification, validation/edit checks, testing, data review/reconciliation, SAE reconciliation, database lock/unlock, vendor data transfers, training, and DM documentation to meet timelines and quality standards.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Lead single-threaded product and technical ownership for Client Intelligence & Data, defining APIs and event-driven architectures to deliver merchant-facing analytics, KPIs, and reports. Drive platform strategy toward AI-driven insights, enforce production reliability and automated QA, champion You Build It You Run It culture, partner cross-functionally to scale multi-tenant analytics capabilities, and prioritize work using evidence-based frameworks.

Perform systems analysis and options analysis for an Intelligence Mission Data project: gather and translate business requirements into system specifications, develop use cases, evaluate technical solutions, ensure integration with business processes, support testing, and prepare reports, briefings, and meeting artifacts for project stakeholders.

The role involves owning product feature development, participating in system design, and maintaining software performance in an agile setting.

Lead the development of data products at Procore, leveraging construction data to create predictive models and insights. Collaborate across teams to define product strategy, data quality standards, and success metrics, while utilizing AI tools effectively.

The Robot Data Operations Analyst will control robots, evaluate performance, provide quality assurance, and document observations safely in an R&D setting.

As a Senior Software Engineer, you will develop core data pipeline components for an AI-native data warehouse, oversee feature delivery, and ensure data quality and reliability.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

As a Senior Software Engineer, you will design and implement backend components for a distributed vector database, optimize performance, and collaborate on real-time analytics systems.

The Senior Systems Engineer will manage technical relationships, oversee pre-sales evaluations, and collaborate with engineering to define product requirements. They will also develop sales strategies and provide customer proposals while demonstrating expertise in storage products and architectures.

The Account Executive will drive sales growth by developing business with enterprise customers, managing relationships, and delivering proposals aligned with their needs, while collaborating with channel partners.

As a Business Development Intern, you will support acquisition activities by validating prospect data, conducting market research, and aiding analysis for software company acquisitions.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

The Staff Data Scientist will lead analytical strategies for Firefox, focusing on product growth, measurement frameworks, and mentoring data scientists while guiding data-driven decisions.

Lead and build Burq's data and ML platform: own warehouse, ingestion, semantic layer, and BI; architect and ship forecasting, optimization, matching, and reliability models; implement feature pipelines, training/serving, and monitoring; drive AI agent initiatives; hire and grow a data/ML team; set governance, intake processes, and partner with product, engineering, and commercial stakeholders to align models with business impact.

Lead people analytics by building end-to-end models and production data pipelines, designing dimensional models, and creating LLM/NLP solutions. Translate statistical outputs into executive-ready insights, develop automated dbt/Snowflake workflows and dashboards, partner with HR systems owners and the enterprise data office, and enforce data governance and privacy for People data to support strategic workforce decisions.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

Seeking a Senior Data Scientist to lead predictive analytics and machine learning initiatives. Responsibilities include building ML models, data management, and mentoring junior data scientists. Must have expertise in AWS and strong statistical knowledge.

Abstract and enter clinical data from healthcare records, apply clinical operations policies, troubleshoot VPN/MFA access, maintain confidentiality, and provide guidance to less-experienced team members while ensuring data quality and workflow adherence.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

Lead full-cycle enterprise sales for data and intelligence consulting: originate pipeline, run discovery, manage complex multi-stakeholder deals, create SOWs with delivery teams, co-sell with partners, and meet revenue targets while leveraging AI tools.