Top Data Jobs in Calgary

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

As a Senior Product Manager, you'll drive product strategy for Wrapbook's tech enablement team, collaborating cross-functionally and managing product roadmaps and execution for critical features.

The role involves designing, building, and deploying machine learning models, collaborating with teams to address business problems, and mentoring other data scientists.

As a Senior Data Engineer, you will build scalable data pipelines, manage cloud infrastructure, and support analytics and data science teams, leveraging various technologies to deliver impactful solutions for clients.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from ad platforms, order systems, and real-time events. Ensure reliability, observability, and maintainability across event-driven and batch architectures, implement authentication flows, optimize data workflows in a cloud-native environment, and collaborate with product, infrastructure, and data teams to onboard new sources.

Proactively explore RevenueCat's data to identify product opportunities, translate ambiguous problems into analyses and production-grade predictive/descriptive models, partner with Product and Engineering to ship data-powered features (LTV prediction, experimentation, benchmarking), define statistical approaches, iterate on models in production, and communicate insights to technical and non-technical audiences.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

Lead Harbor's Data & AI consulting service line for law firms: own P&L and financial performance, develop and productize offerings, oversee delivery and talent development, drive business development and market thought leadership, and ensure measurable client value.

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.

Lead clinical data stewardship for R&D to enforce clinical data standards, govern MDM entities, author policies/SOPs, map metadata/lineage into governance platforms, and advise governance boards to ensure clinical data is FAIR, AI-ready, and regulatory-compliant.

Lead governance, review, and validation of clinical data deliverables ensuring CDISC/SDTM compliance and submission readiness. Oversee EDC/eCRF design, data quality control frameworks, vendor deliverable review, reporting/visualization, and integration of external data sources. Support scalable data platforms, automation, and AI-enabled capabilities while partnering with Data Management, Statistics, and vendors to ensure data traceability and regulatory alignment.

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.

Lead strategic architecture for front-office investment technology and data solutions, advising on platform selection and implementation (Aladdin, Charles River, Bloomberg, etc.), guiding data architecture, governance and quality, managing small-to-medium implementation teams, and ensuring delivery across portfolio management, trading, and reporting domains.

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.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

The Staff Backend Engineer will architect high-throughput streaming systems, define technical direction, mentor engineers, and solve complex problems for Helius' core products.

The Functional Analyst - Data will manage data extraction, validation, and organization from legacy HR systems, ensuring the integrity of archived data and documenting functional requirements while collaborating with technical teams.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

The role involves designing and implementing scalable data models using Data Vault techniques on Azure. Responsibilities include collaborating with stakeholders, optimizing data vault models, ensuring data security, and documenting data processes.

The Senior Data Analytics Engineer will develop reporting solutions, perform data analysis, improve data quality, and collaborate with stakeholders to enhance business metrics understanding. They should have strong SQL skills and at least 7 years of experience in analytics roles.

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

The Monetization Analytics Manager will build data models and dashboards, analyze pricing metrics, support pricing strategies, and automate self-service tools for revenue optimization.

The Data Implementation Manager leads a team for configuring and optimizing an AI-driven platform, overseeing onboarding, integration, and technical solution delivery for customers.