Top Data Jobs in Calgary

Support enhancement and implementation of incident management processes and systems, assist incident investigations, analyze safety performance data to identify trends and risks, contribute to enterprise initiatives and stakeholder engagement, and support reporting, corrective actions, and process improvements to prevent incident recurrence.

Design, build, and scale Snowflake ingestion pipelines and ML/LLM systems. Create agentic tooling to generate, test, and maintain pipelines. Collaborate with analysts, data scientists, and product teams to deliver reliable, high-performance data infrastructure and operationalize models for an AI-first e-commerce platform.

Perform data extraction, transformation, cleansing and imports (CSV/SQL) into Clio, support customer onboarding, troubleshoot escalated migrations, manage multiple client cases, create knowledge articles, partner with enablement and product teams to improve and automate migration processes, and deliver exceptional customer service throughout the migration lifecycle.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Lead an eight-person data conversion team to design, build, test, and validate ETL conversions from legacy systems into Catalis SaaS products. Develop playbooks, mapping standards, estimation tools, and quality controls. Partner with Product, Engineering, Sales, and PSO; adopt AI-assisted tooling and enforce CJIS-compliant data handling and validation practices.

Support end-to-end Power BI report development: gather requirements, design data models and ETL, build dashboards, automate workflows with Power Automate, manage data sources (SharePoint, SQL, APIs), resolve data quality issues, document solutions, and collaborate with stakeholders to improve reporting and processes.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, design A/B and bandit experiments, develop pricing automation (DealBot) and monitoring for AI-driven rate recommendations, own ETL/analysis/visualization, and partner with Finance, Risk, Product, and GTM teams to operationalize pricing intelligence.

Senior individual-contributor Data Scientist building predictive models, AI-powered tools, and self-serve analytics. Responsibilities include SQL/Python modeling, Power BI dashboarding, LLM/Claude integrations, feature engineering, automation, stakeholder communication, and mentoring BI peers to drive measurable business value across sales, retention, finance, operations, and talent.

Lead and grow a data governance function setting standards for ownership, metadata, quality, access, and compliance. Operate DataHub as the canonical catalog, define data quality SLAs and health scores, run audits, manage entitlements, align privacy and legal requirements, run the domain council, and drive cross-functional remediation and training programs.

Own and govern Capital Power's end-to-end forward price curve framework: design, build, validate, and maintain curves; manage curve intake, configuration in ZEMA/Allegro, daily production monitoring, IPV, model validation, and governance reporting to senior committees.

As an iOS engineer, you will improve a scanning engine for security analysis of iOS applications, develop tools for static and dynamic analysis, and contribute to security checks.

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.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.

Design, scope, and implement modern analytics solutions; lead pre-sales, POCs, and client relationships; manage data engineering lifecycle, teams, testing, and cloud data platform integrations to deliver business outcomes.

Lead executive interviews, stakeholder workshops, and current-state assessments to identify operational gaps and opportunities. Develop business cases, operating models, governance, KPIs, roadmaps, and practical AI-enabled solutions. Advise on AI strategy, innovation, commercialization, customer experience, and change management. Support transition of recommendations to delivery teams and occasionally participate in business development.

Evaluate and label model-generated and human-written code outputs, debug and assess code/agent trajectories, prompt models for complex data science tasks, review visualizations, and report quality trends to improve model behavior.

Evaluate and label model-generated and human-written software engineering outputs for coding, debugging, and codebase-related tasks. Assess agent trajectories, prompt models for complex coding tasks, proofread and improve responses, and report quality and performance trends. Part-time contractor role contributing to model development.

Lead financial management and governance for Data & IT investments: budgeting, forecasting, financial modeling, business case stewardship, TCO and benefits analysis, SAP-based cost interpretation, and executive reporting to support portfolio decision-making and value realization.

Lead enterprise data, analytics, AI, automation, and information governance. Define strategy and roadmap, modernize data platforms (lakehouse/Azure Databricks), establish AI and automation capabilities, enforce governance/MDM (Semarchy), deliver BI/Power BI and predictive solutions, run Automation CoE, drive data literacy, and build a high-performing cross-functional team.

Lead advanced analytics projects to build, validate and monitor predictive and descriptive models. Determine technical approaches, evaluate diverse data sources, translate findings for stakeholders, and provide technical leadership and mentorship to analytics teams to support business decisions and risk mitigation.

Support SAP ECC to S/4HANA migration for project data: govern, validate, cleanse, migrate and reconcile data; define integrations; enable transition of legacy reporting to modern analytics (SAP Analytics Cloud, Microsoft Fabric, Power BI); establish data ownership, KPIs and continuous improvement for project reporting and analytics.

Lead development and productionization of large-scale ML and GenAI products. Own end-to-end data science lifecycle: prototyping, model development, benchmarking, deployment, monitoring, and stakeholder communication. Collaborate with domain experts to define metrics, optimize models (including LLM fine-tuning and embedding retrieval), and build scalable pipelines and integrations (OCR, table extraction, multimodal and GNN solutions).

Build and maintain financial and operational datasets and Power BI dashboards; map metrics across eCommerce and engineering sources; support AOP, ARR, pricing and retention modeling; run CI/CD pre-production checks, monitor processes, and partner cross-functionally with Finance, Marketing/Retention, and Product.

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.