Job Description
Job Title: Senior Big Data Developer – Snowflake, Spark & AWS
Location: Toronto
Work Model: Hybrid (4 Days WFO)
Position Overview
We are seeking an experienced Senior Big Data Developer to join the Data Engineering team. You will design, build, and optimize scalable data pipelines and infrastructure to support enterprise data analytics and business intelligence initiatives.
Key Responsibilities
• Design and develop robust ETL/ELT pipelines using Spark, Hive, and Hadoop for large-scale data processing.
• Architect and maintain Snowflake data warehouse solutions, including schema design and optimization.
• Develop and manage infrastructure-as-code solutions using AWS services such as S3, Glue, EMR, and RDS.
• Build and deploy containerized applications using Docker, Kubernetes, and OpenShift (OCP4).
• Implement CI/CD pipelines and version control best practices using Git.
• Collaborate with data scientists and analytics teams to ensure data quality and accessibility.
• Mentor junior team members and contribute to technical documentation.
• Leverage Gen AI tools to enhance code quality and development efficiency.
Required Qualifications
• 5+ years of hands-on experience with Big Data technologies including Hadoop, Spark, and Hive.
• Advanced proficiency with the Snowflake platform and data modeling.
• Strong SQL expertise and database design knowledge.
• Proven experience with AWS Cloud services.
• Programming experience in Scala, Python, or Java.
• Knowledge of Source Code Management (SCM), Infrastructure-as-Code, and CI/CD pipeline implementation.
• Excellent problem-solving, communication, and self-directed work ethic.
Preferred Qualifications
• Experience with orchestration tools such as Apache Airflow.
• Experience with ETL tools such as Informatica or Talend.
• API development experience.
• Expertise in Docker, Kubernetes, and containerization.
• Scripting proficiency in Shell and Python.
• Understanding of Gen AI for code generation.
Requirements
Sailpoint
Big Data Developer – Snowflake, Spark & AWS • Toronto, ON, ca
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