Top Data Jobs in Ottawa

Reviews and evaluates clinical trial data within oncology programs at Syneos Health, supporting drug development and commercialization services. The role operates within a life sciences clinical solutions environment and contributes to accurate, compliant, and high-quality trial data review. Specific day-to-day tasks and qualification requirements are not provided in the job description.

Reviews and evaluates clinical trial data within oncology studies, supporting data quality, consistency, and drug development objectives. Collaborates with clinical solutions and study teams to identify issues, apply therapeutic expertise, and help deliver reliable outcomes for life sciences customers.

Own GTM data accuracy, hygiene, governance, and integrity across Salesforce and related systems. Build data models, pipelines, Power BI or Tableau dashboards, and automated reporting for Sales and executive stakeholders. Analyze pipeline, forecasting, conversion, win/loss, productivity, and eventually Customer Success metrics. Document KPI definitions, train users, resolve workflow bottlenecks, and recommend improvements to data architecture and processes.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Leads the design, development, optimization, and support of enterprise-scale ETL/ELT pipelines and cloud data platforms. Builds Databricks and Spark processing solutions, dimensional data models, SQL transformations, and data quality controls. Troubleshoots production issues, improves performance and reliability, contributes to data architecture, and establishes engineering standards. Collaborates with technical and business stakeholders while mentoring engineers and supporting CI/CD, testing, monitoring, documentation, and modernization of legacy data warehouses.

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.

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.

Lead single-threaded product and technical ownership for Client Intelligence & Data, defining APIs and event-driven architectures to deliver merchant-facing analytics, KPIs, and reports. Drive platform strategy toward AI-driven insights, enforce production reliability and automated QA, champion You Build It You Run It culture, partner cross-functionally to scale multi-tenant analytics capabilities, and prioritize work using evidence-based frameworks.

Design and implement data models, pipelines, and ML systems to power AI agents and analytics. Build, deploy, and monitor machine learning models at scale, integrate Snowflake/AWS and Salesforce Data Cloud, and deliver production-ready data products and views to stakeholders.

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.

Lead optimization and scaling of Snowflake architecture, build resilient ELT/ETL and MLOps pipelines, implement data observability, automate workflows with AI-assisted tools, and design enterprise semantic models to support analytics and commercial data products.

Perform high-level video captioning, action-based timeline segmentation, and visually-verifiable action labeling. Review and correct AI-generated captions, meet accuracy benchmarks, follow strict guidelines, and complete certification.

Leads multidisciplinary data center design projects from proposal through closeout, coordinating engineering teams, schedules, budgets, deliverables, client relationships, design reviews, risk mitigation, quality compliance, contract administration, and change orders. The role supports business development, mentors junior staff, and requires occasional travel across Canada and the United States.

Lead enterprise and domain data modeling across conceptual, canonical, logical, physical, and business models. Translate business concepts into scalable data structures, facilitate stakeholder workshops, establish business glossaries, and align models with governance, metadata, MDM, analytics, AI, reporting, and data stewardship initiatives. Support engineering teams implementing cloud and lakehouse solutions while serving as a domain architecture lead for durable, flexible modern data platforms.

Manage and coordinate security projects and operations for the Corporate Security Office, supporting project lifecycle from planning to close-out. Provide data analysis, site inspections, hardware/software testing, security screenings, and policy/maintenance plan development while coordinating stakeholders and technical teams.

Leads MAU analytics and data science, managing decision scientists and data scientists while setting quality standards. Owns MAU driver modeling, forecasting, causal analysis, experimentation, and exploratory work supporting growth strategy. Establishes consistent analytical practices, partners with revenue, product, engineering, and data engineering leaders, and embeds the team in roadmap planning. Promotes AI-native workflows through coding agents, automation, and analytical tools while coaching team members into strategic advisors.

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.