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Build and maintain cloud cost visibility pipelines and datasets using SQL, Python, AWS/GCP, and Snowflake to power cost-aware decisions for Product, Engineering, and Finance teams.
Build and automate the next-gen analytics platform for a deskless-workforce SaaS, using BigQuery, dbt, Python, and AI-driven tooling to power scalable, self-serve data access.
Build and industrialize ML and optimization models in Python for a full-stack decision-support product, integrating pipelines, testing, and cloud deployment.
Build and maintain data pipelines and applications using .NET (C#), Apache Spark, Databricks, and Delta Lake to process large-scale data efficiently.
Build and maintain Python/Java backend services and data pipelines for Loora’s AI English tutor, including real-time processing, analytics, and AI model training infrastructure.
Leads a DevOps/Platform Engineering team to transform a proprietary AI-driven market model into a Kubernetes-native, self-service infrastructure platform, focusing on scalability, observability, and cross-functional enablement for rapid internal delivery.
This is the broad job description of the job profile. Definitive job description should be reviewed and discussed between you and your manager. Data Engineer Why Join As a Data Analytics Support specialist at OCBC,…
Design and build data pipelines and microservices to feed AI systems, ensuring data quality and reliability for a web/mobile development agency.
Interested in joining one of Canada's top performing asset managers? We are looking for a Senior Data Integration Engineer for an existing vacancy in our IT department, Connor, Clark & Lunn Financial Group…
Build and maintain high-scale data pipelines and cloud infrastructure for a travel-tech company using Python, SQL, Snowflake, Airflow, and Dagster.
Job Title: Senior Cloud Data Warehouse Engineer Location: Montreal, QC (Hybrid – 3 days onsite every week) Employment: Full-time opportunity Experience: 5+ years About VLink: Started in 2006 and headquartered in…
Team Overview: The Controls Engineering, Measurement and Analytics (CEMA) department is responsible for Cyber Risk and Control assessment, management, monitoring, and reporting capabilities across Technology, resulting…
Lead the build-out of scalable ML systems that productionize customer lifetime-value models and simulations for Root Insurance, using Python, cloud infrastructure, and MLOps tooling.
Build and scale ML pipelines and recommendation models in Python/PyTorch to personalize user experiences across Sber’s ecosystem of financial, retail, media and healthcare services.
Builds and maintains a cloud-based data platform for quantum computing research, designing pipelines and infrastructure to integrate heterogeneous measurement data from R&D, manufacturing, and analytics teams.
Build and optimize backend systems and data pipelines in Clojure, using Temporal and Datadog to ensure scalable, reliable data processing for Crossbeam’s ecosystem-led growth platform.
Lead the 0-1 build of an AI-native data infrastructure platform, defining architecture, hiring the team, and shipping production-grade ML/GenAI systems that power core platform capabilities.
Lead a team building Hadrian’s data backbone—ingesting machine and factory data into Snowflake/Iceberg, streaming via Redpanda/Kafka, and orchestrating with Dagster/dbt to power scheduling, analytics, and ML across autonomous factories.
Build and maintain the shared infrastructure that powers Clay’s products, focusing on scale, reliability, and performance for systems handling high concurrency and large-scale data.
Builds and analyzes experiments, predictive models, and metrics for a fast-growing AI-powered B2B SaaS platform, partnering with teams like Product and Marketing to drive data-informed decisions.
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