Job Description
Job Title: AWS Data Engineer with Databricks
Location: Toronto, ON (Hybrid/Onsite)
Experience: 6–10 Years
Employment Type: Contract
Job Summary
We are looking for an experienced AWS Data Engineer with strong Databricks expertise to design, build, and optimize scalable data solutions in a cloud-native environment. The ideal candidate will have hands-on experience in AWS services, Databricks, Spark, and modern data lake/lakehouse architectures.
You will play a critical role in building high-performance data pipelines, ensuring data reliability, and enabling analytics and machine learning use cases.
Key Responsibilities
Design and develop scalable data pipelines using AWS and Databricks.
Build ETL/ELT processes using PySpark/Scala in Databricks.
Implement and manage data lake/lakehouse architecture using AWS S3 and Delta Lake.
Develop batch and real-time data processing pipelines.
Integrate data from multiple sources (RDS, Redshift, APIs, Kafka, S3, etc...
Location: Toronto, ON (Hybrid/Onsite)
Experience: 6–10 Years
Employment Type: Contract
Job Summary
We are looking for an experienced AWS Data Engineer with strong Databricks expertise to design, build, and optimize scalable data solutions in a cloud-native environment. The ideal candidate will have hands-on experience in AWS services, Databricks, Spark, and modern data lake/lakehouse architectures.
You will play a critical role in building high-performance data pipelines, ensuring data reliability, and enabling analytics and machine learning use cases.
Key Responsibilities
Design and develop scalable data pipelines using AWS and Databricks.
Build ETL/ELT processes using PySpark/Scala in Databricks.
Implement and manage data lake/lakehouse architecture using AWS S3 and Delta Lake.
Develop batch and real-time data processing pipelines.
Integrate data from multiple sources (RDS, Redshift, APIs, Kafka, S3, etc...
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