Top Data Jobs in Ottawa

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Design, build, optimize, and maintain scalable Databricks data pipelines and ETL/ELT workflows. Manage CI/CD with Azure Pipelines and Azure Key Vault, improve performance and cost efficiency, implement data quality and governance practices, troubleshoot distributed systems, collaborate with stakeholders, and support cloud data platform modernization initiatives.

Designs statistical analysis plans and validates machine learning models using rigorous performance, calibration, uncertainty, subgroup, fairness, and longitudinal analyses. Applies biostatistical methods to healthcare data, documents assumptions and limitations for auditability and regulatory readiness, and translates complex findings into clinically meaningful insights. Collaborates with engineering, machine learning, data, clinical, and product teams.

Lead the Data Modeling team, focusing on the development of reusable core data models and metrics. Collaborate with various teams to ensure data quality and reliability in analytics and AI/ML. Hands-on role requiring experience in data modeling, SQL, Python, and Spark.

Build and own marketing measurement, attribution, experimentation, and analytics for performance, influencer, and lifecycle marketing. Responsibilities include creating dashboards, debugging attribution across advertising platforms and CRM systems, designing incrementality and A/B tests, analyzing CAC, ROAS, payback, cohorts, LTV, and channel efficiency, developing attribution taxonomies and instrumentation, and translating findings into recommendations for marketing, product, finance, and executive stakeholders.

Lead Mozilla’s Marketing Data Science strategy and roadmap for Firefox. Drive attribution, ROI, campaign measurement, budget optimization, causal lift testing, brand impact analysis, retention and LTV modeling, audience segmentation, reporting infrastructure, dashboards, and scalable data tools. Mentor and develop team members, partner with cross-functional data science and marketing leaders, translate complex analyses into actionable recommendations, and evaluate emerging AI tools to improve workflows and business impact.

Lead the architecture and implementation of complex cloud-based data solutions for clients. Define strategic data roadmaps, support pre-sales engagements as a data engineering subject matter expert, conduct technical interviews, mentor architects and engineers, and establish data standards and operating procedures. The role requires extensive AWS and complex data systems experience, expertise across traditional and modern data technologies, strong documentation practices, and excellent communication.

Manage construction and maintenance of de-identified, FISMA-compliant research datasets; implement secure storage, encrypted transfer, and data retention/destruction. Coordinate with qualitative and regulatory teams, support incident response, and deliver formatted codebooks and CDC-requested dataset formats.

Provide on-site configuration and data management support for NASA AFRC projects: maintain CM plans and repositories, control configuration items and engineering changes, administer CCBs and ACMS/ACCT, run audits (PCAs), track action items and metrics, and train users on CM tools and processes.

Annotate and segment videos, write objective captions, label visually verifiable actions, and review AI-generated captions for accuracy and consistency. Specialists must follow detailed guidelines, maintain at least 95% benchmark accuracy, and complete a paid certification process involving training, platform practice, and five certification tasks before accessing ongoing production work.

CommBank is seeking Indigenous job seekers for various roles across its sectors, offering traineeships, internships, and direct employment opportunities with support from an Indigenous Careers team.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Lead a hybrid engineering and data platform team to build scalable software and data infrastructure. Oversee Power Platform deployments, data architecture, governance and compliance (GDPR/HIPAA), BI/analytics, DevOps automation, and integration of AI/LLM and agentic solutions to drive intelligent automation and platform scalability.

Analyze product usage, feature adoption, telemetry, and financial data to generate actionable insights. Own data modeling, dashboards, KPI development, and end-to-end analytics delivery while partnering with stakeholders on product initiatives. Mentor associate-level analysts and maintain strong execution metrics for analytics work. The role requires advanced SQL and Python, Databricks and PySpark expertise, visualization experience, and SaaS product analytics experience.

Lead the architecture and development of Blackpoint Cyber’s enterprise data platform. Own data ingestion, storage, transformation, governance, observability, lifecycle management, and cost optimization. Design scalable pipelines and medallion architecture for cybersecurity events, survey data, business intelligence, analytics, reporting, and AI. Drive multi-cloud integrations, data quality, reliability, compliance, and platform roadmap decisions while mentoring senior data engineers and collaborating across Product, Engineering, AI, and Security teams.

Perform accurate remote data entry: enter, update, verify, and correct records; organize digital files; process forms and invoices; ensure confidentiality and compliance; meet productivity and accuracy targets; collaborate with team to improve workflows.

Build and maintain scalable financial data infrastructure, including ingestion, validation, normalization, and integrations. Develop systems that calculate portfolio performance metrics efficiently across high-volume datasets, improve reliability and observability, and support distributed processing. Create internal tools, dashboards, reusable schemas, asset data feeds, and self-service analytics capabilities. Collaborate cross-functionally to expand market-data coverage, support B2B integrations, and strengthen operational resilience.

Designs and develops enterprise cloud data solutions, including batch, near-real-time, and API-based pipelines. Builds data models, warehouses, lakes, and lakehouses while implementing governance, quality, lineage, and curation practices. Supports CI/CD, testing, monitoring, observability, security, and compliance. Collaborates with architects, product owners, analysts, and leadership on platform strategy and modernization. Mentors engineers, leads reviews, presents technical topics, and explores AI-enabled data capabilities.

Lead client-facing Workiva implementation projects from discovery through go-live. Manage project delivery, design scalable Workiva solutions, run workshops, configure documents/spreadsheets/workflows, lead teams, support testing and training, and mentor consultants to ensure on-time, high-quality reporting and operational outcomes.

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.

Lead end-to-end data and ML pipelines for onboarding and fraud decisions: ingest streaming and batch sources, build feature platform and entity resolution, productionize ML models, enforce PII/data governance, and set technical direction while mentoring engineers and ensuring low-latency, reliable serving.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

As a Data Analyst, you will analyze user behavior, create interactive dashboards, and collaborate with teams to provide actionable insights for product improvement.

Analyze user behavior and product performance, create reports and dashboards, and provide data-driven insights to teams for decision-making.