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Build and harden data pipelines that ingest and reconcile heterogeneous energy data sources, and deploy applied AI components (LLM-based document extraction, enrichment, decision support) for a Montreal-based SaaS platform for building decarbonation. Core stack: Python, SQL, cloud data warehouse, LLMs.
The Senior QA Automation Engineer will build and evolve quality-control frameworks for data platforms using Python, Selenium, PyTest, Azure Databricks, and Spark SQL. This role focuses on testing complex data movement and enterprise data validation within a treasury and balance sheet management technology team.
This Senior Software Engineer role focuses on building and maintaining scalable data pipelines, offline experimentation tooling, and route simulation services for Lyft's mapping team. The position involves working with technologies like AWS, Databricks, Kubernetes, and Airflow to improve routing accuracy and travel time estimations.
Designs and maintains a graph-RAG platform’s data architecture, including schema, taxonomy, and ingestion pipelines for enterprise content (e.g., SharePoint) while ensuring scalability, accuracy, and cost efficiency.
Tata Consultancy Services Canada Inc. is seeking a skilled Data Integration Developer to design, develop, and maintain robust data pipelines and infrastructure across our enterprise systems. This role emphasizes data…
Lead a data engineering team at Sanofi, designing and operating scalable data pipelines and platforms using Spark, Kafka, Snowflake, and AWS to support analytics and AI/ML use cases in the commercial business.
The Data & AI Engineer will build and industrialize energy data pipelines and develop AI components for production, focusing on data modeling, quality, and decision support within a decarbonization SaaS platform.
Build and deploy AI systems for Nasdaq Lens, focusing on Python, AI agent frameworks, and AWS while ensuring compliance in regulated environments.
Designs and maintains data structures for a graph-RAG platform, builds pipelines for SharePoint/Microsoft data ingestion, and ensures knowledge graph accuracy while optimizing for cost and scalability.
Design and maintain scalable cloud data pipelines using AWS services like EMR, S3, Redshift, and Airflow, with real-time processing via Kafka and Spark Streaming.
Senior QA Automation Engineer designing and maintaining automated testing frameworks using Selenium, PyTest, and Python to ensure data quality across data pipelines, APIs, and Azure cloud data platforms in a hybrid Toronto role.
Builds AI agents and data pipelines in Python/SQL for RBC’s wealth management systems, collaborating with data and DevOps teams to ensure scalability and reliability.
Lead and mentor a full-stack engineering organization, shaping architecture and delivery across multiple teams while partnering with stakeholders worldwide at a last-mile delivery services company.
Senior Full Stack Software Developer building end-to-end web applications for aviation technology, working across the full software lifecycle with AWS, C#, .NET, microservices, and CI/CD.
Senior Full Stack Developer designing and delivering web-based software for aerospace communications, working with AWS, microservices, CI/CD, and various databases/web technologies.
Build and maintain modern web apps using React, Angular, and Java, integrating REST APIs and databases while collaborating in an Agile government IT team.
Senior Python Engineer builds secure, scalable microservices and data pipelines for a bank using FastAPI, PySpark, Azure Databricks, Docker, Kubernetes, Redis, and Kafka.
Senior Full Stack Engineer at a YC-backed creator commerce startup, building and scaling the platform across Python/FastAPI backend and React/TypeScript frontend in an AI-native development environment.
VP of Data Engineering leading data strategy, architecture, and governance across Databricks, Snowflake, and cloud data platforms for an asset management firm, partnering with investment, product, and AI teams.
Lead a cross-functional data engineering team designing and operating scalable ETL/ELT pipelines, managing cloud data platforms (Snowflake, Azure/GCP), and establishing engineering best practices including CI/CD and data governance.
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