Senior AWS Data Engineer - 10+yrs
- Toronto, ON, Canada
Contract
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Job details
- Job type
- Contract
- Apply by
- Experience
- 10-12+ years of experience in Data Engineering.
- Posting language
- English
- Posted
Original job description
Role: Senior AWS Data Engineer - 10+yrs
Location: Toronto, ON
Work Model: Hybrid – 3 Days/Week Onsite
Duration: 12-Month Contract (Extension Possible)
Job Summary
We are seeking a Senior AWS Data Engineer with 10- 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
- 10-12+ 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
- Apache Airflow
- 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.
- Familiarity with CI/CD pipelines and DevOps practices.
- Knowledge of data governance, security, and AWS best practices.
- AWS Certifications are an asset.
Ideal Candidate
- Strong hands-on AWS Data Engineer with proven technical expertise.
- Individual contributor capable of designing and developing scalable cloud data solutions.
- Experience delivering enterprise-grade AWS data platforms in production environments.
- Able to work independently while collaborating effectively with cross-functional teams.
More about this job
Responsibilities
Design, develop, optimize, and support scalable AWS data pipelines, ETL/ELT workflows, data lakes, warehouses, and real-time streaming solutions. Monitor production systems, implement infrastructure as code, and collaborate with cross-functional teams using Agile practices.
Requirements
Requires 10–12+ years of data engineering experience and strong hands-on expertise with AWS data services, Python, SQL, ETL/ELT, and production-grade cloud data platforms. Candidates should also have experience with OLTP and OLAP databases, infrastructure as code, and strong troubleshooting and collaboration skills; banking experience is preferred.
Skills
- AWS Glue
- PySpark
- Python
- Amazon S3
- AWS Lambda
- Amazon Redshift
- Amazon DynamoDB
- Amazon Kinesis
- Apache Kafka
- Apache Airflow
- SQL
- ETL/ELT
- Infrastructure as Code
- AWS CDK
- Terraform
- Data Engineering
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- AWS
- AWS Glue
- PySpark
- Python
- Amazon S3
- AWS Lambda
- Amazon Redshift
- Amazon DynamoDB
- Amazon Kinesis
- Apache Kafka
- Apache Airflow
- SQL
- ETL/ELT
- Data Engineering
- Data Lakes
- Data Warehousing
- Real-Time Streaming
- OLTP
- OLAP
- Infrastructure as Code
- AWS CDK
- Terraform
- Production Data Platforms
- Banking
- Financial Services
- CI/CD
- DevOps
- Data Governance
- Agile
- Cloud Data Solutions