Top Data Jobs in Calgary

Design and deliver enterprise-scale EDW and BI solutions, ensuring performance and scalability, while mentoring teams and engaging stakeholders.

Perform product analytics by analyzing large datasets, running A/B tests, building dashboards, applying statistical methods and ML for forecasting and segmentation, and communicating insights to product, sales, and customers to drive adoption and product improvements.

Lead and manage client data and digital strategy projects end-to-end: plan and run projects, produce C-level deliverables, coach and evaluate teams, perform advanced data analysis, define client needs, pitch solutions, and develop business proposals to grow accounts.

The Engineering Manager will lead cross-functional teams of engineers, focusing on building high-performing environments, managing technical delivery, fostering team growth, and ensuring data-driven strategies.

Lead and develop a team to govern and validate clinical data builds, vendor deliverables, and data integrations. Implement and maintain CDASH/SDTM/ADaM standards, validation libraries, and submission-ready processes. Oversee data ingestion into the Clinical Data Warehouse, drive automation (SAS, Python, AI), maintain SOPs/QMS, and partner with Biostatistics, Data Management, Standards, and CROs to ensure high-quality, analysis-ready datasets.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Deliver front-office investment technology consulting: requirements, workflow design, system configuration, integration, testing, and handover. Provide subject-matter expertise on OMS/EMS/PMS platforms, data architecture, cloud integrations, and program governance to ensure timely, on-budget transformations.

Lead data-driven underwriting improvements by analyzing claims, risk signals, and underwriting data; build statistical and ML models for cyber risk assessment, pricing, and automation; produce dashboards and reports; collaborate with actuarial, product, and engineering teams; mentor teammates and lead cross-functional initiatives to optimize underwriting and risk selection.

Lead optimization and scaling of Snowflake architecture, build resilient ELT/ETL and MLOps pipelines, implement data observability, automate workflows with AI-assisted tools, and design enterprise semantic models to support analytics and commercial data products.

The Data Analyst will support business needs through technical problem-solving and data analysis, focusing on improving user experience and conversion rates in a B2B2C environment.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Lead end-to-end debit analytics: design and modernize reporting, build executive dashboards, run A/B tests, produce actionable insights, optimize measurement/KPIs, mentor analysts, and partner with stakeholders to influence product and business decisions using cloud data platforms and advanced SQL/Python analytics.

Lead labeling quality and methodology for ML at Coalition: design annotation tasks, define quality frameworks (IAA, gold standards), manage Label Studio and vendor BPOs, partner with ML/data teams, and track operational metrics to improve accuracy and throughput.

Design and build data models, pipelines, and ML systems for production. Integrate Snowflake/AWS with Salesforce Data Cloud, deploy and monitor models (MLOps), and deliver data products and dashboards to enable AI-driven automation across the platform.

As a Data Annotation Specialist, you will label, audit, and optimize data for AI models in Chinese while ensuring high accuracy and quality. You will perform repetitive tasks and collaborate with teams, providing feedback and recommendations for data improvement.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Lead single-threaded product and technical ownership for Client Intelligence & Data, defining APIs and event-driven architectures to deliver merchant-facing analytics, KPIs, and reports. Drive platform strategy toward AI-driven insights, enforce production reliability and automated QA, champion You Build It You Run It culture, partner cross-functionally to scale multi-tenant analytics capabilities, and prioritize work using evidence-based frameworks.

Designs, integrates, and implements process-data solutions for upstream oil and gas. Leads OT-based initiatives, manages agile project delivery, gathers requirements, delivers ETL/big-data/visualization solutions, hands over to sustainment teams, drives continuous improvement, liaises with stakeholders, and mentors junior staff.

The role involves owning product feature development, participating in system design, and maintaining software performance in an agile setting.

Lead the development of data products at Procore, leveraging construction data to create predictive models and insights. Collaborate across teams to define product strategy, data quality standards, and success metrics, while utilizing AI tools effectively.

The Robot Data Operations Analyst will control robots, evaluate performance, provide quality assurance, and document observations safely in an R&D setting.

As a Senior Software Engineer, you will develop core data pipeline components for an AI-native data warehouse, oversee feature delivery, and ensure data quality and reliability.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

As a Senior Software Engineer, you will design and implement backend components for a distributed vector database, optimize performance, and collaborate on real-time analytics systems.

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.