puestos de Machine Learning Engineer en Canadá

Title: AWS Data Engineer

Location: TORONTO, ON.

Terms: Contract

• Design and build scalable data pipelines using AWS services like AWS Glue, Amazon Redshift, and QS / SNS / Cloudwatch / Step function / CDK (or Terraform).
• Develop efficient ETL processes for data extraction, transformation, and loading into data warehouses and lakes.
• Create and manage applications using Python, PySpark, SQL, Databricks, and various AWS technologies.
• Automate repetitive tasks and build reusable frameworks to improve efficiency.
• Involved in Architecture Design and Review, Team Leadership Skills, Management Skills, Code Review & Sign-Off.
• Code & Architecture Review - Ensuring quality and scalability of code / data pipelines.
• Team Leadership Skills - Leading sprint planning, retrospectives and assigning and reviewing tasks.
• Project Management Skills - Agile / Scrum methodology, risk & deadline management.
• Mentoring & Coaching - Upskilling team on AWS best practices and data architecture.
• Stakeholder Communication - Translating tech into business value and reporting to non-technical managers.

• SQL - Expert (Must have)
• AWS (Redshift / Lambda / Glue / SQS / SNS / CloudWatch / Step function / CDK (or Terraform)) - Expert (Must have)
• Pyspark - Intermediate / Expert
• Python - Intermediate (Must have or Pyspark knowledge)
• Strong Communication Skills

• Code & Architecture Review - Ensuring quality and scalability of code / data pipelines.
• Exposure to cost optimization strategies in AWS, Data Lake vs. Data Warehouse Architecture, Designing Scalable ETL Pipelines, Real-Time Data Ingestion, Data Partitioning and Performance Optimization, Security and Compliance, Data Quality.