Top Data Jobs in Ottawa

Design and lead scalable enterprise data architectures using PostgreSQL and graph databases. Define logical and physical data models, optimize performance, modernize databases, integrate relational and graph systems, support AI/analytics platforms, produce governance documentation, and guide engineering teams through implementation.

Design end-to-end cloud-native AI and data platform architectures enabling Digital Twin and Knowledge Graph solutions. Lead architecture discussions, define scalable platform patterns, collaborate with AI/data/infrastructure teams, evaluate emerging AI technologies, produce technical documentation, and support solution discovery and roadmap planning.

Own and drive the architecture and roadmap of ClickUp's data platform. Build scalable, reliable data pipelines and AI/ML infrastructure using AWS serverless, Snowflake, dbt, and Terraform. Lead cross-team technical initiatives, optimize cloud costs, establish engineering standards (observability, testing, CI/CD), mentor senior engineers, and influence org-wide architecture decisions.

Lead clinical data management from study start-up to database lock, oversee DM deliverables and teams, liaise with sponsors, manage timelines/budgets/scope, mentor staff, ensure GCP/SOP compliance, coordinate cross-functional biometrics activities, support audits, and drive process improvements and client satisfaction.

Designs, builds, and maintains scalable batch and real-time data pipelines supporting an IoT safety ecosystem. The role manages ETL/ELT processes, data lakes, warehouses, lakehouses, orchestration, monitoring, data quality, and observability. It partners with product, engineering, analytics, and data science teams to deliver reliable data services, productionize models, and shape long-term data platform architecture using AWS and modern infrastructure practices.

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.

Perform end-to-end data conversions for CityView implementations: map source-to-target data, develop reusable conversion scripts, troubleshoot issues, coordinate with customers and project teams, and deliver tested conversions to test and production environments while following CityView methodology and timelines.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Own go-to-market strategy and adoption for Stripe's data products. Develop positioning, messaging, competitive intelligence, launch plans, demand programs, and sales enablement. Translate customer and market insights into roadmap recommendations and measurable KPIs while partnering cross-functionally to drive commercialization and growth.

Evaluate and rank multimodal model outputs, stress-test and document failures, author and edit dataset prompts/responses, build and apply rubrics, perform high-quality annotations across text, image, and structured formats, participate in calibration checks, adapt to evolving tasks, and report model performance trends to cross-functional teams.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Implement and configure enterprise Workday HCM solutions, lead the data workstream including gathering, transforming and loading organizational and employee data, liaise with customers and internal stakeholders, deliver data solutions, support sales and practice improvements, and educate others within the Workday practice.

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.

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.

Design and maintain enterprise semantic models and AI-ready data products, build and optimize Power BI datasets and DAX metrics, enforce governance and security, enable self-service and AI-assisted analytics, and collaborate with stakeholders and data engineers to support BI and ML integrations.

Design, build, and operate large-scale security data pipelines, lake/lakehouse storage, and analytics to normalize telemetry from a massive GPU fleet. Ensure data platform security (encryption, RBAC/ABAC, audit), enable trustworthy analytics and detection, collaborate across teams to define data contracts, and maintain data quality, provenance, and freshness for security posture and automated response.

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.

Design, build, and maintain scalable data pipelines, optimize Databricks/Spark and Delta Lake architectures, deliver trusted datasets for analytics and ML, implement observability and data quality, and drive platform architecture and team mentorship.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

The Product Data Analyst will analyze operational data, develop analytics frameworks, create dashboards in Tableau, ensure data integrity, and collaborate across teams to enhance decision-making and reporting.

Design and operate distributed inference systems for LLMs, build large-scale data pipelines, and debug production issues while collaborating with researchers and ML engineers.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

Lead and grow SQUIRE's Data organization as a player-coach, owning long-term data architecture, building reliable Snowflake pipelines, setting standards for modeling and data quality, hiring and budgeting for a 5+ person team, partnering cross-functionally, auditing integrations, and enabling AI/LLM use cases while remaining hands-on for high-risk technical work.

Owner of Float's Snowflake architecture and ingestion layer: build orchestration, observability, data quality and contracts, CI/CD for data code, support ML pipelines, and collaborate with analytics, data science and product teams to deliver reliable, cost-efficient, governed data.