Data Engineer
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Job Title: Data Engineer
Job Type: Full Time
Location: Toronto, ON (Onsite)
Job Description
We are seeking an experienced Data Engineer with strong data warehouse expertise and extensive experience in the banking and financial services domain. The ideal candidate will have 12+ years of experience in data engineering and hands-on expertise designing and developing scalable data pipelines, data lakes, and data warehouses on AWS.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and workflows on AWS
- Build and manage data lakes and data warehouses using Amazon S3 and Redshift
- Develop ETL/ELT processes using AWS Glue, Lambda, Spark, and related technologies
- Implement Kafka message processing, batch data ingestion, and business-layer data processing
- Optimize data ingestion, transformation, and loading processes
- Ensure data quality, governance, security, performance, and scalability
- Monitor and troubleshoot data pipelines and workflows using AWS services
- Automate deployments through CI/CD pipelines
- Collaborate with clients, data users, and stakeholders to understand requirements
- Develop reusable data engineering frameworks and design patterns
- Perform data onboarding using established frameworks
- Analyze existing IBM Netezza code and design migration solutions for AWS Data Lake
- Develop unit tests and support QA, SIT, and performance testing
Required Skills & Experience
- 12+ years of experience in data engineering/data warehousing
- Strong experience in the banking and financial services domain
- Hands-on expertise with Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift
- Experience with AWS Step Functions, IAM, and CloudWatch
- Strong ETL/ELT and data pipeline development experience
- Experience with IBM Netezza and migration to AWS environments
- Knowledge of Kafka, Spark, and batch data processing
- Strong understanding of data warehouse architecture and data lake solutions
Good to Have
- AWS Solutions Architect or Data Analytics certification
- Experience with Airflow or Amazon MWAA
- Exposure to Snowflake, Databricks, or Delta Lake
- Experience with CI/CD and cloud deployment practices
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