Top Data Jobs in Calgary

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

Own cloud operational health, architecture intelligence, and cost optimization. Analyze cloud spend, build dashboards/reporting, enforce governance, review architecture for cost impact, and translate technical findings for engineering, finance, and executives.

Design, build, deploy, and maintain production-grade measurement and ML systems (MMM, incrementality, insights, recommendations). Translate statistical and causal methods into scalable products, debug full-stack data and model issues, evaluate methodology tradeoffs, and collaborate with engineering, product, and customer teams while providing customer-facing technical support.

Lead end-to-end data and ML pipelines for onboarding and fraud decisions: ingest streaming and batch sources, build feature platform and entity resolution, productionize ML models, enforce PII/data governance, and set technical direction while mentoring engineers and ensuring low-latency, reliable serving.

The Enterprise Solutions Manager drives operational excellence and client success through strategic analysis, process optimization, and project management, collaborating with various teams to deliver AI solutions.

Support data management and governance by managing data assets, ensuring data quality, standards, and policies; publish and protect data for analytics; contribute to analytic platforms and reporting solutions; work on moderately complex projects with general guidance.

Lead design and implementation of Jane's customer data infrastructure: own event collection, pipelines, CDP tooling, schema governance, identity resolution, and attribution. Work cross-functionally with marketing, BI, product, and engineering to set standards, evaluate tooling (e.g., RudderStack), ensure privacy-compliant instrumentation, and build reliable, consistent data delivery to the warehouse.

Manage technical data for IP Routing hardware NPI programs: support NPI from data entry through factory implementation, maintain product data and Engineering Change Orders across the product lifecycle, and coordinate with engineering, supply chain, and manufacturing to ensure accurate PLM/PDM records and implementation.

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.

Own and evolve Narvar's data pipelines, platforms, and data products on GCP. Design, build, and operate ETL/ELT workflows, data models, and embedded analytics using BigQuery and Airflow. Improve data quality, observability, lineage, and prepare datasets for LLM/AI use cases while collaborating cross-functionally and driving architectural decisions.

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.

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.

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.

Design and optimize SQL Server solutions, manage data, automate processes with PowerShell, and integrate with external systems to enhance functionality.

As a Backend Engineer on the Data team, you will design and maintain data pipelines and services, ensuring data quality and scalability while collaborating with cross-functional teams to meet data needs.

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

Lead a distributed team of data scientists and engineers, focusing on data infrastructure and ML systems while collaborating with product and marketing teams.

Manage relationships with strategic healthcare clients, oversee complex projects, innovate operational processes, and lead large teams to improve AI training and application.

Own analysis and algorithmic solutions for ads delivery; train, deploy, and scale ML/optimization models into production; build logging, monitoring, and lineage; improve data pipelines; mentor data scientists; use agentic AI tools daily; collaborate with engineers to integrate models into ads systems and handle on-call production incidents.

Perform clinical data management for Phase I-IV studies: design and test eCRFs/EDC, develop edit checks and DMPs, manage queries, reconcile external data and SAEs, support database lock, and collaborate with cross-functional teams and vendors.

Design and lead enterprise data architecture for agentic AI, including hybrid lakehouse and graph/vector integrations. Define schemas and knowledge graphs, ensure database performance and governance across Snowflake/Kinetica/BigQuery, establish ETL/ELT and CDC/streaming strategies, and act as technical client lead for architecture, security, and performance benchmarks.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

Lead Life360's Data Engineering organization and own end-to-end data platform and analytics engineering strategy. Define architecture for ingestion, transformation, modeling, and serving data for humans and LLMs. Manage engineering managers and teams, drive self-serve data capabilities, cost management, vendor decisions, data quality/governance, and partner cross-functionally to prioritize engineering work that drives business impact.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.