Job Description

Role: Lead AWS Data Engineer- SQL Expert , ETL, Python
Location: Toronto
Hybrid

AWS, SQL, OLAP, OLTP, ETL , PYTHON

Responsibilities:


Design, develop, and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Redshift, EMR, etc.)


Collaborate with data scientists, analysts, and business stakeholders to gather requirements and build ETL/ELT workflows.


Optimize data workflows for scalability, reliability, and performance.


Ensure data quality, governance, and security standards are met.


Monitor and troubleshoot data pipeline issues.


Required Skills:


8+ years of experience in data engineering, preferably in a cloud environment.


Strong hands-on experience with AWS services: Glue, Redshift, S3, Lambda, EMR, Athena.


Proficient in Python and SQL.


Experience with data modeling, warehousing concepts, and data lakes.


Familiarity with orchestration tools like Airflow or Step Functions.


Knowledge of CI/CD practices and version control (e.g., Git).


Nice to Have:


Experience with real-time data processing (e.g., Kinesis, Kafka).


Knowledge of Terraform or CloudFormation for infrastructure as code.


Familiarity with DevOps practices and tools.

AWS, SQL, OLAP, OLTP, ETL , PYTHON

Responsibilities:


Design, develop, and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Redshift, EMR, etc.)


Collaborate with data scientists, analysts, and business stakeholders to gather requirements and build ETL/ELT workflows.


Optimize data workflows for scalability, reliability, and performance.


Ensure data quality, governance, and security standards are met.


Monitor and troubleshoot data pipeline issues.


Required Skills:


8+ years of experience in data engineering, preferably in a cloud environment.


Strong hands-on experience with AWS services: Glue, Redshift, S3, Lambda, EMR, Athena.


Proficient in Python and SQL.


Experience with data modeling, warehousing concepts, and data lakes.


Familiarity with orchestration tools like Airflow or Step Functions.


Knowledge of CI/CD practices and version control (e.g., Git).


Nice to Have:


Experience with real-time data processing (e.g., Kinesis, Kafka).


Knowledge of Terraform or CloudFormation for infrastructure as code.


Familiarity with DevOps practices and tools.