Top Data Jobs in Ottawa

Lead design and implement a scalable Medallion lakehouse on GCS and Databricks. Build and govern ingestion and transformation pipelines (Astro/Airflow, PySpark, Delta Live Tables), apply domain-driven data modeling, manage Unity Catalog access and lineage, collaborate with analytics and vendors, and proactively surface risks with clear documentation.

The VP of Data & AI Engineering leads Duck Creek's enterprise data and AI strategy, overseeing global teams, implementing scalable platforms, and ensuring data governance and responsible AI practices.

Lead analytics for Internal Audit Claims: extract, transform, reconcile, and validate large claims datasets; build and maintain Power BI reports/dashboards; perform QA and tie-outs; support automation, bots/AI enablement, and executive reporting; mentor other analysts and partner with audit, IT, and business stakeholders to deliver repeatable, validated analytics.

The Software Engineer will provide technical support to customers, collaborate with engineering teams, and drive customer success initiatives while leveraging Python and SQL expertise.

Lead design and delivery of end-to-end ML solutions for insurance (claims, underwriting, sales). Own feature engineering, model selection, training, validation, and handling imbalanced/weak-label data. Ensure explainability, governance, and production readiness. Act as client-facing data scientist, coordinate offshore teams, contribute to MLOps, model monitoring, and deployment on cloud analytics platforms.

As a Data Annotation Specialist, you will label, audit, and optimize data for AI models in Chinese while ensuring high accuracy and quality. You will perform repetitive tasks and collaborate with teams, providing feedback and recommendations for data improvement.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

Lead the data and ML product vision: define roadmap, prototype models on noisy behavioral datasets, translate signals into user-facing features, partner with engineering to productionize ML, and generate insights to inform product roadmaps.

Build and operate a reliable data platform: monitor infrastructure and pipelines, automate platform tasks, manage IaC and CI/CD, support RBAC and governance, contribute to data pipelines and migration, document runbooks, and participate in on-call incident response while improving AI-assisted engineering workflows.

Build statistical and predictive models to measure and optimize marketing, sales, and customer success impact on pipeline, bookings, ARR, retention, and expansion. Analyze paid media performance and conversion funnels, design experiments and causal measurement, forecast revenue, partner with cross-functional teams to define metrics, and communicate data-driven recommendations to senior leadership while improving measurement methodologies and data quality.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

The Data Platform Marketing Manager will lead marketing strategies for DoiT's data lake and Snowflake optimization business, aiming to drive growth and impact.

Lead data analysis, migration planning, and data quality for a province-wide CIS migration. Develop ETL specs, perform data profiling, manage stakeholder collaboration, and ensure accurate, compliant migration of legacy hospital data into the new Clinical Information System.

Lead design, development, and deployment of GenAI and NLP solutions (RAG, LLM-powered apps, agentic AI, Document Intelligence). Work with clients to translate business needs, build end-to-end ML pipelines, mentor teams, present results to stakeholders, and operationalize scalable, governed AI systems.

Design and own end-to-end Azure-based data platform architecture using Databricks. Define ingestion, transformation, governance (Unity Catalog), and delivery standards; optimize performance and cost; integrate with Azure ecosystem and Power BI; mentor teams and guide delivery and CI/CD practices.

Research, evaluate, and manage partnerships with data providers. Assess datasets for coverage and interoperability, support deal structuring, maintain partnership pipeline, and collaborate with product, engineering, and legal to integrate data into the platform.

Build and operate scalable data ingestion, transformation, and connector frameworks; design and maintain a knowledge-graph-based data fabric; normalize and vectorize enterprise data for LLM/AI workflows; implement governance, lineage, access controls, and secure APIs to serve ML/agent pipelines.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

Lead and grow a full‑stack engineering team building customer data and identity solutions. Own architecture, APIs, component libraries, code quality, hiring, mentoring, roadmap execution, and cross‑functional collaboration. Contribute code for high‑impact items and ensure scalable systems and agile best practices.

Design and build scalable, semantically consistent 360 entity data models and transformation pipelines. Implement cleansing, enrichment, KPIs, scoring, and business rules in SQL and Python/Scala, ensure data quality, lineage, and performance at scale. Use AI coding assistants and SDD to accelerate development, create tests and documentation, and collaborate with domain experts, data scientists, and product teams to deliver trusted, reusable data assets.

Design, build, deploy, and maintain production-grade measurement and ML systems (MMM, incrementality, insights, recommendations). Translate statistical and causal methods into scalable products, debug full-stack data and model issues, evaluate methodology tradeoffs, and collaborate with engineering, product, and customer teams while providing customer-facing technical support.

The Senior Web3 Data Analyst will manage web3 analytics, monitor on-chain activity, analyze competitor metrics, and deliver insights for product and leadership teams.

Design business data models and data architectures, mentor data teams, translate business requirements into technical specifications, and set standards for AI-augmented development practices.