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Lead Data Engineer at Brillio | JobVerse
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Lead Data Engineer
Brillio
Website
LinkedIn
Lead Data Engineer
Canada
Full Time
2 hours ago
$80 - $85 CAD
Visa Sponsorship
Apply Now
Key skills
Airflow
Apache
AWS
Azure
Cloud
Docker
ETL
Google Cloud Platform
Kafka
Kubernetes
Python
SQL
AI
GenAI
RAG
Agentic
AutoGen
LangGraph
ELT
Data Engineering
Data Warehousing
Analytics
Snowflake
Apache Airflow
dbt
Google Cloud
Git
CI/CD
About this role
Role Overview
Design, build, and maintain scalable data pipelines and data platforms.
Develop AI-powered data solutions using Agentic AI and Multi-Agent architectures.
Build and optimize intelligent workflows using Snowflake Cortex capabilities.
Integrate LLMs with enterprise data while ensuring governance and security.
Design semantic search, RAG, and AI-assisted analytics solutions.
Develop and optimize Snowflake data models, stored procedures, and performance tuning.
Collaborate with Data Scientists, AI Engineers, Product Managers, and business stakeholders to deliver AI-enabled data products.
Ensure data quality, reliability, observability, and security across data platforms.
Automate deployment using CI/CD pipelines and Infrastructure as Code where applicable.
Stay current with emerging AI, GenAI, and Snowflake technologies and recommend best practices.
Requirements
5+ years of experience in Data Engineering or Data Platform Development.
Strong experience working with cloud-based data platforms and modern data architectures.
Agentic AI application development.
Multi-Agent Orchestration frameworks.
Snowflake Cortex (Cortex AI, Cortex Analyst, Cortex Search, Cortex Functions).
Snowflake Data Cloud.
SQL and advanced query optimization.
Python programming.
ETL/ELT pipeline development.
Data modeling and data warehousing.
REST APIs and system integrations.
Git and CI/CD practices.
Experience with LangGraph, CrewAI, AutoGen, or similar multi-agent frameworks.
Experience with LLMs and Retrieval-Augmented Generation (RAG).
Knowledge of vector databases and semantic search.
Experience with Azure, AWS, or Google Cloud Platform.
Apache Airflow, dbt, or similar orchestration tools.
Docker and Kubernetes.
Streaming technologies such as Kafka.
Tech Stack
Airflow
Apache
AWS
Azure
Cloud
Docker
ETL
Google Cloud Platform
Kafka
Kubernetes
Python
SQL
Apply Now
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