Top Data Jobs in Ottawa

The Senior Systems Engineer will manage technical relationships, oversee pre-sales evaluations, and collaborate with engineering to define product requirements. They will also develop sales strategies and provide customer proposals while demonstrating expertise in storage products and architectures.

The Account Executive will drive sales growth by developing business with enterprise customers, managing relationships, and delivering proposals aligned with their needs, while collaborating with channel partners.

As a Business Development Intern, you will support acquisition activities by validating prospect data, conducting market research, and aiding analysis for software company acquisitions.

Own and operate the data plane: develop Envoy/WASM filters for deep packet inspection, deploy and manage EKS workloads with Helm/GitOps and CI/CD, integrate Redis sidecars, provide observability (Prometheus/Grafana/OpenTelemetry), ensure reliable audit log streaming, and author ADRs as the data plane evolves.

Design and implement automated validation and testing frameworks for data connectors; modernize connector platforms; investigate and resolve authentication, connectivity, and performance issues; build diagnostics, telemetry, and CI/CD to improve reliability and quality across cloud and on-premises data sources; mentor and contribute to engineering best practices.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.

Lead and build Burq's data and ML platform: own warehouse, ingestion, semantic layer, and BI; architect and ship forecasting, optimization, matching, and reliability models; implement feature pipelines, training/serving, and monitoring; drive AI agent initiatives; hire and grow a data/ML team; set governance, intake processes, and partner with product, engineering, and commercial stakeholders to align models with business impact.

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

Lead people analytics by building end-to-end models and production data pipelines, designing dimensional models, and creating LLM/NLP solutions. Translate statistical outputs into executive-ready insights, develop automated dbt/Snowflake workflows and dashboards, partner with HR systems owners and the enterprise data office, and enforce data governance and privacy for People data to support strategic workforce decisions.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

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.

Analyze business performance and consumer behavior, define and track KPIs, perform deep dives and trend analysis, build dashboards and reports, partner with business leaders to shape consumer strategy, and present actionable insights.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Abstract and enter clinical data from healthcare records, apply clinical operations policies, troubleshoot VPN/MFA access, maintain confidentiality, and provide guidance to less-experienced team members while ensuring data quality and workflow adherence.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

Senior data analyst/programmer using SAS or R to analyze commercial claims and EHR real-world data. Create longitudinal cohorts, derive baseline/outcome variables, assess data quality, apply epidemiologic study designs and statistical methods (regression, survival), review protocols/SAPs, and program TFLs. Familiarity with OMOP CDM and OHDSI tools is a plus; prior pharmaceutical experience preferred.

Lead full-cycle enterprise sales for data and intelligence consulting: originate pipeline, run discovery, manage complex multi-stakeholder deals, create SOWs with delivery teams, co-sell with partners, and meet revenue targets while leveraging AI tools.

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 product execution for retail platforms, integrations, and data foundations. Establish data governance, define integration patterns and data contracts, improve fulfillment/OMS capabilities, evaluate vendors, and enable analytics and AI-driven automation to increase operational efficiency.

Perform product and player-behavior analysis for Marvel Strike Force using SQL/Python and reporting tools. Build recurring KPI reports, design/validate analytics tracking and experiments, partner with cross-functional teams, and use AI-enabled tools to accelerate workflows while ensuring data quality, privacy, and clear executive-ready insights.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

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.