Apptoza Inc.
Senior AWS Data Engineer
- Compensation
- Not disclosed
- Location
- Toronto, Canada
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Contract
- Experience
- 12+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 12+ years of experience in Data Engineering.
- Strong hands-on experience with:
- AWS Glue (PySpark/Python)
- Amazon S3
- AWS Lambda
- Amazon Redshift
- Amazon DynamoDB
- Amazon Kinesis and/or Apache Kafka
- SQL
- Python
- Strong understanding of ETL/ELT development.
- Experience working with OLTP and OLAP databases.
- Hands-on experience with Infrastructure as Code (AWS CDK or Terraform).
- Experience building and supporting production-grade AWS data platforms.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and collaboration skills.
Nice to have
- Experience in the Banking or Financial Services domain.
- Experience with real-time event-driven data architectures.
- Familiarity with CI/CD pipelines and DevOps practices.
- Knowledge of data governance, security, and AWS best practices.
- AWS Certifications are an asset.
Full description
Duration: 12-Month Contract (Extension Possible)
Job Summary
AWS, SQL, OLAP, OLTP, ETL , PYTHON
We are seeking a Senior AWS Data Engineer with 12+ years of hands-on experience designing, developing, and supporting enterprise-scale data platforms on AWS. The ideal candidate will be a strong individual contributor with deep expertise in AWS data engineering, ETL development, and real-time data streaming technologies.
This role requires someone who can quickly understand business requirements, build scalable data pipelines, optimize data processing, and support production-grade cloud data solutions in a fast-paced banking environment.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using AWS services.
- Build and optimize ETL/ELT workflows using AWS Glue (PySpark/Python).
- Develop serverless data processing solutions using AWS Lambda.
- Design and manage data lakes using Amazon S3.
- Develop and optimize data warehouse solutions using Amazon Redshift.
- Work with Amazon DynamoDB and other AWS data services for high-performance applications.
- Build and support real-time data streaming solutions using Amazon Kinesis and/or Apache Kafka.
- Develop, schedule, and monitor workflows using Apache Airflow.
- Write complex SQL queries and optimize database performance across OLTP and OLAP systems.
- Implement Infrastructure as Code (IaC) using AWS CDK or Terraform.
- Monitor, troubleshoot, and support production data pipelines.
- Collaborate with cross-functional teams to deliver reliable and scalable data solutions.
- Follow Agile development practices and participate in sprint planning, code reviews, and technical discussions.
Required Skills
- 12+ years of experience in Data Engineering.
- Strong hands-on experience with:
- AWS Glue (PySpark/Python)
- Amazon S3
- AWS Lambda
- Amazon Redshift
- Amazon DynamoDB
- Amazon Kinesis and/or Apache Kafka
- SQL
- Python
- Strong understanding of ETL/ELT development.
- Experience working with OLTP and OLAP databases.
- Hands-on experience with Infrastructure as Code (AWS CDK or Terraform).
- Experience building and supporting production-grade AWS data platforms.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and collaboration skills.
Preferred Qualifications
- Experience in the Banking or Financial Services domain.
- Experience with real-time event-driven data architectures.