Top Data Jobs in Ottawa

You will architect and develop new features for SELECT, focusing on cost management, UI components, data visualization, and improving application performance.

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

Design and implement ETLs to process large volumes of customer data, build tools for integration, and mentor team members to improve data handling and scalability.

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.

Seeking a Senior Data Scientist to lead predictive analytics and machine learning initiatives. Responsibilities include building ML models, data management, and mentoring junior data scientists. Must have expertise in AWS and strong statistical knowledge.

Lead and manage the strategy, development, and operation of BECU's Enterprise Data Platform, ensuring secure and scalable data capabilities while fostering team collaboration and data governance.

As a Senior Data Scientist in Marketing Analytics, you'll partner with Marketing to solve problems, design data-driven solutions, lead experimentation, communicate insights, and operationalize solutions for business impact.

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.

As a Data Scientist in Product Analytics, you will analyze large datasets, improve user experience, conduct A/B tests, and collaborate with teams to drive product insights and customer engagement.

Design and analyze large-scale A/B and causal studies, build predictive and decision models, apply learning analytics and psychometric methods to measure learner outcomes, partner with product and engineering to instrument data and drive product decisions.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Design, build, and maintain scalable Databricks-based ETL/ELT pipelines and data models optimized for AI/ML. Manage orchestration, data quality, governance, and CI/CD (ADO → GitHub) while collaborating with cross-functional teams in Agile delivery.

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.

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.

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, 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.

Lead platform and data strategy by defining microservice platform services, API contract and governance, Snowflake lakehouse direction, and data monetization. Partner with architecture, engineering, analytics, and commercial teams to drive platform performance, scalability, international readiness, and developer experience while influencing cross-functional teams without direct authority.

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.

As a Staff Software Engineer, you'll architect and build foundational platform services, focusing on data infrastructure, healthcare interoperability, and secure APIs while mentoring other engineers.

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

The Data Governance Intern will assist in developing enterprise data catalogs, documenting data elements, and supporting data quality efforts using SQL and Python.

The AI Data Expert will review and evaluate AI-generated outputs and textual content, ensuring cultural relevance and quality. Responsibilities include content analysis, assessing multimedia materials, and providing structured annotations while adhering to detailed guidelines. Native fluency in French and strong English skills are essential, with previous experience in AI evaluation preferred.

Evaluate and review AI outputs, generate or assess content, and ensure cultural relevance and accuracy in various media for AI projects.