Top Data Jobs in Ottawa

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.

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

Lead teams designing, developing, and supporting safety-critical air traffic management software and data systems (CAATS/SMI). Provide people and technical leadership, manage requirements, testing, configuration, budgets, and ensure system safety and operational alignment.

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

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 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 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.

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.

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.

Lead and grow a Data Engineering team to build production data pipelines, medallion datasets, and reusable data products. Drive architecture, engineering standards, design reviews, and cross-functional delivery. Partner with Product, Analytics, Data Science, and Platform to enable governed, reliable data foundations for analytics and AI. Mentor engineers and manage multiple concurrent initiatives to deliver predictable outcomes.

This role involves deploying solutions for clients, managing data compliance, and providing feedback for product improvement. Requires collaboration with teams and clients.

Lead RWD analysis strategy and execution: develop technical specifications and statistical programs, perform complex observational analyses (propensity scoring, ML), validate cohorts/variables, ensure QC, collaborate cross-functionally, and communicate results to non-technical stakeholders.

The Senior Data Platform Engineer will design and operate a unified data platform, ensuring reliable data flows and collaborating across teams to shape data strategy and architecture.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

The Data Engineer will assist clients with SAP security design, implement SAP security, develop authorization profiles, and conduct security reviews.

Perform quantitative and qualitative data analysis and reporting to support public health research and program evaluation. Produce reports, integrate mixed-methods data, assess implementation measures, advise stakeholders, manage gov/admin systems, and present findings to decision-makers.

Own technical execution of customer data migrations: explore source systems, export data, author declarative version-controlled mappings, transform and validate data, run end-to-end migrations on internal platform, build reusable templates/validation, troubleshoot discrepancies, and document mapping and transformation logic for auditable production cutovers.

Lead the Data Platform product for AISim, owning ingestion, schema reconciliation, lineage/provenance, sensitivity and field-of-use governance, federated data sharing, experiment-integration APIs, and dataset usability metrics. Partner with engineering, science, design, and compliance to turn ambiguous data problems into measurable, scalable platform features.

Lead roadmap and deliverables for measurement products (attribution, ABM, first-party data), create 0→1 solutions, write clear product specs, and drive features to completion working with engineers, designers, QA, and cross-functional teams.

Join the centralized Analytics team to measure product features, build and maintain dashboards, analyze clickstream and behavioral data, support A/B testing and feature measurement, and communicate insights to Product, Engineering, and Design. Grow technical skills with mentorship and contribute to Generative BI and AI-assisted analytics workflows.