Top Data Jobs in Ottawa

Leads and develops an enterprise sales team responsible for strategic seller acquisition, pipeline generation, complex deal execution, forecasting, revenue growth, and repeatable upmarket sales motions. Partners cross-functionally with product, solutions engineering, legal, finance, marketing, partnerships, implementation, and customer success. Coaches enterprise account executives, manages strategic opportunities, improves deal quality, and uses market insight to influence product, pricing, and go-to-market strategy.

Leads and develops an enterprise sales team responsible for strategic seller acquisition, pipeline generation, complex deal execution, forecasting, and revenue outcomes. Builds repeatable sales motions, coaches Enterprise Account Executives, manages territory and account strategies, leads high-value negotiations, and partners cross-functionally with product, legal, finance, marketing, implementation, and customer success teams. Uses market insight to influence product, pricing, partnerships, and go-to-market strategy.

Lead and develop five experienced analysts and data scientists while personally owning analytics across ecommerce, health, and supply chain. Partner with executives, establish KPI and reporting standards, prioritize the analytics roadmap, deliver strategic insights, and advance AI-native self-service analytics tools. The role combines people leadership, hands-on analysis, data governance, and business strategy in a remote-first environment.

Own and evolve a portable data platform infrastructure across commercial cloud, government cloud, and on-premises environments. Responsibilities include infrastructure as code, security and compliance, observability, SLOs, incident response, capacity planning, backups, upgrades, deployment tooling, and runbooks. The role will establish SRE practices, support regulated customer deployments, collaborate with distributed systems engineers, and mentor a future SRE hire.

Own Treasury’s data architecture and technical roadmap, personally building and operating a Snowflake liquidity datamart with source integrations, data models, reconciliation, controls, and data contracts. Partner with machine learning engineers on forecasting datasets and lead the Treasury Management System build-versus-buy recommendation. The role requires production reliability, automation, incident response, stakeholder management, and translating ambiguous financial business problems into adopted systems.

Own Treasury’s data architecture and hands-on development of a Snowflake liquidity datamart. Build integrations, data models, reconciliation logic, data quality controls, forecasting datasets, and production pipelines. Partner with Treasury, Accounting, and machine learning engineers; lead Treasury Management System build-versus-buy recommendations; and operate reliable, controlled data systems through adoption. The role also includes automation, monitoring, incident response, and reducing manual reconciliation and investigation.

Design, build, and operate shared backend platforms and frameworks for data acquisition, processing, and access. Lead projects from architecture through production, develop event-driven and batch or streaming systems, and improve reliability, observability, scalability, and data quality. Collaborate with software engineers, data engineers, and data scientists, make architectural trade-offs, mentor engineers, and contribute to technical standards. The role may also involve external data integrations and analytics and machine-learning data systems.

Owns credit policy development and governance for Square Financial Services, including underwriting strategy, policy experimentation, portfolio monitoring, regulatory documentation, and risk reporting. Designs rigorous champion-challenger tests, randomized holdouts, and staged rollouts while balancing growth, losses, profitability, fair lending, and bank oversight requirements. Partners with Risk, Compliance, Internal Audit, and senior leadership to scale credit products responsibly.

Leads GitLab’s Product, Sales, and Finance Data Science teams, managing managers and a 12-person organization. Sets data science standards, prioritizes investments, partners with executives, drives product adoption and revenue growth, and oversees experimentation, causal inference, predictive modeling, and AI initiatives. Develops talent, builds succession, and collaborates with Analytics Engineering and Data Engineering on a shared data and AI roadmap.

Develop and maintain Ericsson products and services by contributing to requirements analysis, system and software design, integration, verification, documentation, and cloud-based solution development. Responsibilities include CEE10 design, SDI3 upgrades, solution design and integration, GDCE development, collaboration, coaching, mentoring, and innovation.

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.

Leads GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

The Data Scientist will partner with Sales, Revenue Operations, and Finance to analyze GTM performance, build and productionize machine learning models, conduct experiments, forecast outcomes, and identify growth opportunities. Responsibilities include statistical analysis, causal inference, Python and SQL development, MLOps, agentic workflow automation, semantic-layer contributions, executive reporting, and communicating insights to nontechnical stakeholders in a fully remote environment.

Build and maintain pipelines that extract and organize engineering knowledge from repositories and documents. Develop PostgreSQL and vector search, retrieval evaluation, ranking, and review workflows while protecting restricted content. Connect the knowledge base to project tools and collaborate with embedded designers. After the initial platform build, contribute to client projects involving embedded Linux, drivers, applications, and test tooling. The role requires Python, SQL, Git, Linux, AI coding-tool experience, strong communication, and enthusiasm for embedded hardware.

Designs, develops, and operationalizes secure, scalable data pipelines and data products for Government of Canada environments. Responsibilities include Databricks-based ingestion, transformation, batch and streaming processing, Delta Lake optimization, data quality controls, cloud and on-premises integration, ETL modernization, CI/CD, testing, deployment, monitoring, and knowledge transfer.

Designs and builds industrial digital-thread integrations connecting SAP, Tekla PowerFab, MES, machine telemetry, and shop-floor systems. Develops canonical ISA-95-aware data models, OPC UA/MQTT/PLC connectivity, streaming pipelines, AWS data lakes, and master-data mappings for digital twins. Validates integrations using vendor emulators and live plant systems, establishes data standards, and partners with OT and security teams on compliant OT/IT convergence.

Build and operate Block’s data platform, including warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop reliable Python services, developer tools, and Terraform infrastructure for petabyte-scale data. Partner with data practitioners and product teams, establish engineering standards, provide technical direction, and mentor engineers while ensuring security, reliability, observability, usability, and data governance.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Manage data partnerships end to end, including sourcing opportunities, vendor outreach, requirements definition, contracting, data transfers, updates, and issue triage. Collaborate with modeling and annotation teams, oversee external data scraping vendors, facilitate dataset handoffs, product manage novel data collection methods, and develop scalable processes and tools. The role requires experience managing data vendor programs, AI data supplier relationships, data analysis, data management, and cross-functional collaboration.

Serve as the technical anchor for Domino’s identity and authorization platform. Design scalable, relationship-based authorization using SpiceDB; guide migration from legacy access checks; build cloud-native identity integrations; improve platform reliability, security, and architecture; and advise engineering teams on authorization, APIs, abstractions, and AI-assisted development practices.

Analyze qualitative survey responses about chemical engineering academic programs by anonymizing, segmenting, grouping themes, and synthesizing findings. Create and maintain a database covering courses, learning outcomes, and potential program modifications. The role requires organizational skills, independent work, attention to detail, proficiency with Microsoft collaboration and office tools, and availability for training and assigned work.

Maintains HR data integrity within an ERP system, conducts data quality reviews and audits, investigates discrepancies, supports reporting and process improvements, and coordinates HR administrative activities including onboarding, learning, engagement, surveys, meetings, and events. The role also responds to internal enquiries, collaborates with HR, Finance, and IT, and provides operational support for HR programs and services.

Provides presales technical expertise for HPE storage solutions, including solution architecture, proposals, demonstrations, presentations, training, and customer migrations or integrations. Supports sales specialists and channel partners, maintains customer relationships, achieves sales KPIs and quotas, and advises on data lifecycle management, virtualization, application stacks, public cloud, backup, and ransomware protection. Requires deep storage-industry expertise and competitive knowledge.

Own enterprise business development and revenue growth for physical AI data and solutions across North America. Build pipeline, engage technical and executive buyers, lead discovery, develop proposals, secure paid pilots, negotiate contracts, close and collect revenue, and expand accounts. The role carries an individual quota and requires coordination with technical, delivery, and product teams, alongside strong commercial judgment and familiarity with robotics, embodied AI, autonomy, sensors, computer vision, and AI data.

Lead presales architecture engagements by conducting technical discovery, translating business needs into scalable technology solutions, developing proposals and estimates, supporting sales opportunities, and coordinating transitions into delivery. The role spans cloud, infrastructure modernization, platform engineering, containerization, cybersecurity, data, and AI. It requires client-facing communication, technical solution design, delivery estimation, partner collaboration, and the ability to align technical recommendations with business outcomes and commercial expectations.