We are looking for an experienced AWS Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate will have solid hands-on experience with AWS, Python, PySpark, SQL, and ETL/data engineering .
Must-Have Skills
- AWS
- AWS Glue
- PySpark / Apache Spark
- Python
- SQL
- ETL / ELT
- Data pipeline development
- Amazon S3
- AWS Lambda
- AWS Step Functions
- Data Warehousing
- Data modeling
- Experience with large-scale data processing
Responsibilities
- Design and develop scalable data pipelines using AWS Glue, PySpark, Python, and SQL .
- Build and maintain ETL/ELT workflows for enterprise data platforms.
- Develop data processing solutions using Apache Spark/PySpark .
- Integrate data from multiple structured and unstructured sources.
- Develop serverless solutions using AWS Lambda and Step Functions .
- Store and manage data using Amazon S3 and other AWS data services.
- Optimize data pipelines for performance, reliability, and cost.
- Implement data quality, validation, monitoring, and error-handling processes.
- Work with data analysts, architects, developers, and business stakeholders.
- Participate in code reviews, testing, deployment, and production support.
Required Qualifications
- 5+ years of experience in Data Engineering.
- Strong hands-on experience with AWS Data Engineering services .
- Strong experience with AWS Glue and PySpark .
- Advanced SQL and Python skills.
- Experience developing production-grade ETL/data pipelines.
- Strong understanding of data warehousing and data modeling.
- Experience working with large datasets and distributed processing.
- Strong communication and problem-solving skills.
📌 AWS Data Engineer (Toronto)
🏢 Ku0026K Talents
📍 Toronto
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