Top Data Jobs in Calgary

Build and operate production data pipelines and dimensional data models using Spark and SparkSQL. Own pipelines from requirements through deployment, monitoring, and iteration; improve data quality, lineage, reliability, and cost efficiency. Partner with data scientists, analysts, product managers, and engineers to support datamarts, KPIs, reporting, and analysis. Participate in a business-hours on-call rotation and contribute to runbooks and alerting.

Sets the technical vision for data science, leads complex credit risk, pricing, and loss forecasting models from conception through production, and architects scalable machine learning pipelines. Partners with senior stakeholders to shape strategy, establishes modeling and validation standards, mentors technical staff, and communicates recommendations to executives. The role requires deep fintech lending experience, advanced statistical and machine learning expertise, and hands-on production model deployment.

Design and build scalable backend systems, APIs, data models, event-driven services, experimentation platforms, and personalization systems. Partner with Product, Data Science, Analytics, and Design teams to support customer acquisition and engagement. Establish secure, observable, high-performance engineering practices, mentor junior engineers, and participate in monitoring, on-call, and operational support.

Leads partner-led and enterprise sales growth, primarily through AWS and Microsoft ecosystems. Builds strategic partnerships, develops enterprise accounts, drives end-to-end sales cycles, expands SMB sales processes, positions cloud and digital engineering capabilities, and manages pipeline forecasting. The role also helps shape sales strategy, organization, and scalable go-to-market processes.

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.

Lead data science initiatives for Risk and Support Operations by analyzing customer and product data, defining metrics, forecasting demand, evaluating experiments and risk policies, and building decision frameworks. Use AI tools and agent workflows to improve analytical efficiency. Partner with product, engineering, and risk teams, communicate insights to senior stakeholders, establish technical standards, mentor data scientists, and support hiring.

Build and ship production AI systems across retrieval, knowledge graphs, inference, agentic workflows, and data platforms. Develop customer-context retrieval, scored signals, workflow automation, evaluation, and observability capabilities. Work hands-on with Python, SQL, dbt, lakehouse data, cloud infrastructure, model selection, and inference-cost optimization. Establish reusable engineering patterns and mentor teams through high-quality code and system design.

Analyze product, customer, risk, and support data to guide decisions across Block’s platforms. Own metrics, forecasting, staffing models, experiments, visualizations, and measurement frameworks. Evaluate risk models and policies for performance, bias, and drift; use AI tools and agent workflows to improve analytical execution. Partner with product, engineering, and risk stakeholders, lead technical standards, build reusable tooling, mentor data scientists, and contribute to hiring.

Drive strategic federal sales growth across DISA 4th Estate and Intelligence Community accounts. Responsibilities include pipeline development, account planning, opportunity and win strategy, stakeholder relationship development, acquisition navigation, RFI and solicitation support, CRM management, forecasting, and translating technology solutions into mission outcomes. The role requires expertise in long-cycle federal sales, procurement processes, secure environments, and technology solutions.

Build and deploy Azure-based data pipelines and products for operational data. Implement CI/CD, validate data quality and security, monitor pipeline performance, resolve legacy-system migration challenges, optimize cloud costs, maintain documentation, and support incident response. The role requires collaboration across teams, strong coding and data engineering skills, cloud platform experience, database design knowledge, and familiarity with Azure services and enterprise controls.

Build Precision AI’s first dedicated data platform, covering lakehouse architecture, AWS-based ingestion, orchestration, data quality, lineage, versioning, and cost optimization. Develop reliable pipelines for drone imagery and telemetry, enable reproducible ML training datasets, and establish engineering standards. Later, extend the platform for business analytics with warehousing, dbt, and semantic modeling. This is a hands-on senior individual contributor role based in Calgary with hybrid headquarters attendance.

Build, operate, and improve AIMCo’s modern data platform and Azure services. Develop CI/CD pipelines, automation, developer tooling, Infrastructure as Code, observability, and operational processes. Support data integration, ingestion, streaming, platform reliability, security, performance, and cost optimization. Troubleshoot incidents, document procedures, evaluate technologies, and collaborate with Data, AI, Architecture, Cloud Services, Governance, and business teams using Agile and DevOps practices.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, LTV, and next-best-action decisioning. Design reliable signal contracts covering freshness, provenance, confidence, eligibility, and calibration. Lead feature pipelines, model serving, experimentation, monitoring, and feedback loops while evaluating fairness, risk, compliance, trust, and long-term customer impact. Collaborate across product, growth, data, platform, modeling, risk, and compliance teams.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, lifecycle intelligence, and next-best-action decisioning. Design reliable signal contracts with freshness, provenance, confidence, and calibration guarantees. Lead experimentation, monitoring, feedback loops, and impact evaluation focused on fairness, trust, risk, compliance, and long-term engagement. Partner across product, growth, data, platform, modeling, risk, and compliance teams.

Lead the design, development, and evolution of Helcim’s data platform. Build scalable production data pipelines, advance MLOps and AI infrastructure, improve platform reliability and observability, automate governance, and support data quality, privacy, and security. Translate ambiguous challenges into execution plans, influence architecture, mentor engineers, and drive technical projects from discovery through delivery.

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.

Leads product marketing strategy, positioning, messaging, go-to-market execution, AI adoption, product launches, market expansion, and customer-driven roadmap input. Builds and manages a high-performing product marketing team, partners with executive, product, revenue, and marketing stakeholders, and drives product adoption, retention, category growth, and revenue across programmatic advertising and martech markets.

Supports Regulatory Applications by strengthening data governance, quality, reporting, dashboards, analytics, process improvement, workflow optimization, automation, and responsible AI adoption. Partners with stakeholders to map processes, identify inefficiencies, translate complex data and systems into actionable insights, and implement practical business improvements that support regulatory decision-making.

Build and maintain scalable, tested data models using SQL, dbt, and cloud data warehouses. Partner with Product, Revenue Operations, Finance, Data Engineering, and other stakeholders to translate business needs into trusted datasets. Establish data quality monitoring, documentation, governance, and modeling standards while supporting analytics, reporting, self-service data use, and AI-ready products. Use AI-powered development tools to improve productivity and code quality.

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 the strategy, roadmap, architecture, and adoption of the company’s central data infrastructure and BI platform. Partner with analytics, engineering, and business teams to establish trusted KPI reporting, semantic models, scalable warehousing, BI and ETL tooling, clear SLAs, and AI-powered self-service insights. Translate ambiguous needs into testable requirements, evaluate technical solutions, prototype quickly, and measure adoption, quality, and reporting efficiency.

Develops, operates, troubleshoots, and modernizes enterprise data integrations using Talend. Responsibilities include building ETL/ELT pipelines, APIs, batch and real-time jobs, SQL transformations, scheduling, monitoring, production support, incident resolution, data quality, root-cause analysis, and platform maintenance. The role collaborates with technical and business stakeholders across development, testing, and production environments, while applying AI and automation to improve pipeline development, testing, monitoring, and documentation.

Lead enterprise client reporting and manage Proof’s data team. Own report accuracy, delivery, client relationships, data pipelines, shared models, BI tooling, and internal data insights. Coach team members, guide technical decisions, review SQL and data models, partner with Engineering and Product, resolve reconciliation issues, and improve automation. The role will establish data quality standards and help the company use trusted data to support growth, internal tools, and AI systems.

Build and operate Ground News’s data platform, including warehouse integrations, scalable dimensional models, analytical layers, and KPI infrastructure. Own ingestion pipelines, data quality, monitoring, incident response, infrastructure as code, and deployment workflows across AWS and GCP. Partner with analysts, ML engineers, and product stakeholders to create reliable, reusable data models and ensure accurate, observable, cost-effective data systems.