Top Data Jobs in Ottawa

Lead and grow a team of data analysts while owning analytics strategy, architecture, and delivery. Design and build solutions using Power BI, Databricks, and Azure data services, advise clients on digital transformation, establish repeatable frameworks, and drive measurable client outcomes. Serve as the primary client-facing analytics lead and partner with engineering and product teams.

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.

Lead and execute end-to-end Salesforce data migration projects: define strategy, design and validate data models, build ETL pipelines, resolve data quality issues, perform reconciliation and validation, document mappings, and coordinate cross-functional teams to ensure compliant, accurate migrations on schedule.

As a Data Engineer, you'll design, build, and maintain data pipelines, ensure data quality, and collaborate with stakeholders to deliver data solutions.

Lead and grow a small data team while remaining hands-on in data engineering, analytics engineering, and infrastructure. Own data strategy, warehouse architecture, pipelines, modeling, and self-serve analytics. Partner cross-functionally to deliver trusted metrics, experimentation, and applied ML capabilities (search, recommendations, personalization). Drive adoption of data quality, documentation, self-service, and modern data practices.

Support international data initiatives by performing SQL-based analysis, producing insights and executive-ready scorecards, maintaining reporting/operational dashboards, coordinating incident management and operational readiness, and aligning cross-functional stakeholders to drive data-driven decisions across global markets.

Label and review 2D images and 3D sensor (LiDAR) data using annotation tools to create bounding boxes, cuboids, and other shapes. Ensure annotations follow guidelines, correct or reject pre-labeled data, provide notes, learn internal tools, and collaborate to improve data quality for autonomous vehicle AI.

Design, build, and maintain scalable data ingestion pipelines, databases and data lakes for credit and lending datasets. Ensure accurate data mappings, monitoring and alerting, translate stakeholder requirements into analytical data flows, and integrate APIs to deliver reliable, high-quality data products.

Design, develop, and deliver analytical data products using advanced analytics, statistical modeling, AI/ML, and data mining. Collaborate with stakeholders and data engineers to prepare data, build predictive and prescriptive models, and create dashboards/visualizations to drive business decisions.

Build and own a versioned, documented gold data layer from lakehouse silver tables for AI research. Transform, validate, and productize multi-modal datasets and pipelines (Databricks/PySpark) to support model development, evaluation, and production ML/LLM workflows while ensuring data quality, provenance, and regulatory controls.

Embedded within a core business area, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-driven recommendations to influence product, growth, AI, or partnerships.

Embed in a business unit to define analytical problems, build metrics/reports/experiments, pull and interpret data, surface insights, and drive recommendations to improve product, growth, AI/automation, or partnerships.

Embedded on a business unit, define problems and metrics, run analyses and experiments, build reports, surface insights, and drive data-informed decisions across growth, product, AI, and partnerships.

Embed with a business unit to define problems, build metrics, run analyses and experiments, generate insights, and drive data-informed decisions end-to-end to improve growth, product, AI automation, or partnerships.

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

Embed with a core business area to define problems, build metrics, run analyses and experiments, deliver data-driven recommendations, and drive outcomes end-to-end across growth, product, AI, or partnerships.

Embedded on a business unit (growth, product, AI, or partnerships) to define problems, set metrics, build reports, run analyses and experiments, surface insights, make recommendations, and drive end-to-end execution to improve key business metrics.

Embedded on a core business team, own analytics end-to-end: define problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-informed recommendations to improve growth, product, AI/automation, or partnerships.

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 design and delivery of scalable data lakes, warehouses, and pipelines. Define governance, quality, monitoring, and CI/CD. Build real-time streaming systems and production AI/ML data flows (embeddings, vector stores, RAG, feature stores). Mentor engineers, set platform strategy, and drive data platform modernization.

The Data Migration Specialist will manage end-to-end data migrations, ensuring data quality and effective communication with clients and internal teams while resolving challenges.

The Data Product Manager defines the reporting roadmap, manages KPI alignment, collaborates cross-functionally, ensures data quality, and leads continuous improvement in analytics processes.

Evaluate and label model-generated and human-written software engineering outputs for coding, debugging, and codebase-related tasks. Assess agent trajectories, prompt models for complex coding tasks, proofread and improve responses, and report quality and performance trends. Part-time contractor role contributing to model development.

As Data Privacy & Product Counsel, you will develop and execute privacy strategies, navigate laws like GDPR/CCPA, scale privacy programs, provide guidance on product innovation, and negotiate data protection terms.