Top Data Jobs in Ottawa

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

The Engineering Manager will lead the data platform team, driving architectural decisions, optimizing systems for performance, and collaborating cross-functionally to enhance data usability and value.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Lead and coordinate client legacy data integration into TELUS Health systems. Oversee conversion tasks, ensure data quality, run workshops, identify gaps, propose process changes, escalate issues, prioritize conversion work, and report progress and risks to project management.

Lead and scale Scribd's Data & Analytics organization across Product Analytics, Data Science, and Analytics Engineering. Build operating model, data governance, experimentation frameworks, AI-native workflows, and infrastructure to accelerate insight delivery. Develop director-level leaders, recruit talent, and embed data-driven decision-making at the executive level to drive growth, retention, and portfolio-wide strategy.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Design and deploy predictive models and segmentations using statistical and ML/AI methods. Prepare, clean, and feature-engineer data from warehouses, develop and operationalize models, create visualizations and presentations, document rules, and advise stakeholders to inform business decisions and improve data management tools.

The Senior Data Engineer designs and supports databases for an IVR platform, ensuring performance and scalability while collaborating with multiple teams on data availability and integrity.

Design, build, and maintain scalable batch and streaming data pipelines and domain-oriented data models using dbt and cloud warehouses. Ensure data quality, documentation, and usability for analytics, ML, and reporting while collaborating with Product, Analytics, and ML teams.

Design, build, and maintain robust terabyte-scale data pipelines and stream-processing applications. Collaborate with product teams, participate in full SDLC, automate tests and deployments, monitor operations, and contribute to technical strategy and continuous improvement. Participate in on-call rotation.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

The Data Architect will lead data storage strategy and design across a multi-product SaaS platform, ensuring data architecture unification, optimizing data storage, and supporting AI initiatives while mentoring engineers for self-sufficiency.

As a Data Analyst at Stripe, you'll build data products, metrics, and dashboards, analyze large datasets, and communicate insights to drive business decisions.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The role involves designing and implementing analytics strategies, managing tracking and reporting for ecommerce clients using GA4, GTM, SQL, and Python. The strategist collaborates with internal teams and clients, ensuring analytics support business decisions and measurement frameworks for omnichannel marketing.

Design and build operational data systems, including pipelines, storage layers, and APIs for near real-time enforcement and insights, balancing streaming and batch paradigms.

Design and optimize data pipelines, lead machine learning feature integration, mentor junior engineers, and enforce data governance.

The Senior Product Manager will oversee integration of structured data into the AlphaSense platform, manage product lifecycle, and liaise between technical and user needs. Extensive experience in fintech or financial services required.

The Staff Software Engineer will design, develop, and maintain scalable cloud-based solutions, manage data ingestion and retrieval, and lead architectural innovation while collaborating with cross-functional teams.

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.

Embedded on a core business team, you will define problems, build metrics, run analyses and experiments, produce reports and insights, and drive data-informed decisions end-to-end. You will partner with product, growth, AI, and partnerships teams, communicate findings to leadership, and own outcomes from analysis through execution.

Embedded within a core business area, you will define problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end to improve growth, product, AI/automation, or partnerships.

Own the end-to-end analytical function for a business unit (growth, product, AI, or partnerships): define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions with stakeholders to deliver measurable business impact.