Top Data Engineer Jobs in Calgary

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.

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.

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

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

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Responsible for designing, building, and maintaining scalable data pipelines using Databricks. Optimize ETL/ELT processes and ensure data quality, governance, and security.

Build and maintain scalable, reliable data systems and pipelines, uphold SLOs, partner with Product/Sales/Finance, enable self-service analytics, contribute to data platform strategy, and improve engineering practices for testing, reliability, and documentation.

Own and drive the architecture and roadmap of ClickUp's data platform. Build scalable, reliable data pipelines and AI/ML infrastructure using AWS serverless, Snowflake, dbt, and Terraform. Lead cross-team technical initiatives, optimize cloud costs, establish engineering standards (observability, testing, CI/CD), mentor senior engineers, and influence org-wide architecture decisions.

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.

Owner of Float's Snowflake architecture and ingestion layer: build orchestration, observability, data quality and contracts, CI/CD for data code, support ML pipelines, and collaborate with analytics, data science and product teams to deliver reliable, cost-efficient, governed data.

Design and operate distributed inference systems for LLMs, build large-scale data pipelines, and debug production issues while collaborating with researchers and ML engineers.

Build and maintain core financial backend systems (trading, ledger, billing), transaction processing, reconciliation, and portfolio state management. Design and scale real-time and batch data pipelines, architect APIs and backend services, ensure reliability and observability, and contribute to distributed system design (event-driven, microservices, streaming). Partner with ML teams as needed.

Design, build, and operate cloud-native, serverless ClickHouse database infrastructure. Develop and maintain Kubernetes operators, improve metrics pipelines, support data ingestion/transformation (Spark/Kafka), collaborate with core DB and data plane teams, and ensure scalable, highly available distributed systems with production on-call responsibilities.

As a Staff Software Engineer, you'll architect and build foundational platform services, focusing on data infrastructure, healthcare interoperability, and secure APIs while mentoring other engineers.