Top Data Jobs in Ottawa

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

The Senior Software Engineer will manage data systems, develop scalable pipelines, ensure data security, and build self-service applications for users at Coinbase.

Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met.

As a Senior Data Scientist, you will lead AI risk assessments, coordinate with stakeholders, and ensure effective AI governance practices for safe financial application deployment.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Lead the Public Sector sales team, achieve quotas, implement sales plans, forecast revenue, and cultivate customer relationships.

The Senior Staff Software Engineer will architect Affirm's lakehouse analytics platform, implement data governance, mentor engineers, and collaborate cross-functionally to optimize data infrastructure and solutions.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Design, build, and scale Snowflake ingestion pipelines and ML/LLM systems. Create agentic tooling to generate, test, and maintain pipelines. Collaborate with analysts, data scientists, and product teams to deliver reliable, high-performance data infrastructure and operationalize models for an AI-first e-commerce platform.

Ensure health, stability, and performance of production data platform: respond to incidents, monitor and alert, manage pipelines and APIs, enforce data validation and quality checks, optimize processing performance, collaborate on AWS infrastructure, maintain runbooks/documentation, and support downstream data consumers across multiple business data sources.

Lead the Data + ML Platform team to design, build, and operate scalable data and MLOps infrastructure. Drive platform strategy, enable ML experimentation-to-production workflows (model registry, feature stores, drift monitoring, experiment tracking), modernize streaming and batch pipelines, and scale the team while partnering cross-functionally to deliver measurable outcomes.

Lead design and implementation of shared, reusable data models and a certified metrics layer. Standardize pipeline patterns, CI/CD, and governance; modernize orchestration and observability; partner with Data Science, Infrastructure, and Product to deliver reliable analytics pipelines and enable AI-native data development.

Lead Andela Academy, scaling enterprise learning solutions in AI and Cloud. Build relationships, oversee team delivery, and drive revenue growth with high client satisfaction.

As the Senior Data Scientist for AI & Model Risk, you will lead AI risk assessments, coordinate with stakeholders, evaluate AI system designs, and ensure compliance with risk management principles in financial services.

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Lead BI analyst leveraging a modern data stack to deliver dashboards, automated reports, and AI-driven insights. Partner with stakeholders to define data needs, build Tableau visualizations, write complex SQL in Snowflake, and integrate Snowflake Intelligence/Claude to automate workflows and enable self-service analytics across the company.

As a Sr. Data Engineer, you'll design and manage data pipelines, enhance data quality, and leverage AI to streamline operations, driving the success of our AI growth platform for real estate.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.

In this role, you will define and execute the go-to-market strategy, drive growth, and lead customer success efforts at Reflow, a workplace intelligence platform.

As a Product Manager at Reflow, you will lead product strategy, execution, and delivery while ensuring customer engagement and managing engineering dependencies in an early-stage startup environment.

Design, build, and maintain SparkSQL/PySpark data pipelines in the central data lake to ingest IoT, product, and unstructured data (video/audio). Produce reliable computed tables for analytics, model training, and dashboards; integrate external datasets; ensure high data quality and uptime; and collaborate with Data Science, ML, and cross-functional teams.

Lead end-to-end data science initiatives: design, deploy, and monitor ML/statistical models for credit risk, pricing, collections and fraud. Collaborate cross-functionally to integrate models into production, define model development standards, mentor team members, and maintain scalable ML pipelines and monitoring systems to drive measurable business impact.

Design, build, and operate large-scale Spark/PySpark data pipelines and the enterprise data platform. Implement data integrations, transformations (Python/SQL), monitoring, and data quality. Build MCP servers and AI-enabled tooling, optimize performance, mentor engineers, and lead cross-functional data projects to enable analytics and automation.

Lead the development and execution of the NA digital transformation and data strategy, enhancing capabilities in AI and digital technologies across the business.