AWS Data Engineer || Toronto, ON (Hybrid) || Contract.
Role summary
We are seeking a skilled AWS Data Engineer on a contract basis for a 6-12 month engagement in Toronto, ON. The role requires strong experience in modifying and building scalable data pipelines on AWS, including ETL/ELT workflows. You will work with large datasets, integrate data from various sources, and ensure data quality, integrity, and performance. Collaboration with data architects, analysts, and business stakeholders is key, as is implementing data governance, security, and compliance best practices. The position is hybrid and requires expertise in Python/PySpark, SQL, and AWS services like S3, Glue, Lambda, Redshift, EMR, and Step Functions.
Job Title: AWS Data Engineer
Location: Toronto, ON (Hybrid)
Job Type: Contract (6–12 Months, Possible Extension)
Domain: Banking – MUST
Job Summary:
We are seeking a skilled
AWS Data Engineer
to join our team on a contract basis. The ideal candidate must have strong experience in
modifying existing data pipelines and building new scalable pipelines
on AWS. You will work closely with data architects, analysts, and business stakeholders to ensure efficient data flow, transformation, and availability.
Key Responsibilities:
- Modify, optimize, and maintain existing
data pipelines
in AWS
- Design and develop
new scalable and reliable data pipelines
from scratch
- Build and manage
ETL/ELT workflows
using AWS services
- Work with large datasets to ensure data quality, integrity, and performance
- Integrate data from multiple sources including APIs, databases, and third-party systems
- Monitor pipeline performance and troubleshoot issues proactively
- Collaborate with cross-functional teams for data requirements and delivery
- Implement best practices for
data governance, security, and compliance
Required Skills & Experience:
- 10-12+ years of experience in
Data Engineering
- Strong hands-on experience with
AWS services
such as:
- S3, Glue, Lambda, Redshift, EMR, Step Functions
- Expertise in building and modifying
data pipelines (batch & real-time)
- Proficiency in
Python and/or PySpark
- Experience with
SQL and data modeling
- Hands-on experience with
ETL/ELT tools and frameworks
- Familiarity with
workflow orchestration tools
(e.g., Airflow)
- Experience working in
Agile environments
Nice to Have:
- Experience with
streaming technologies
(Kafka, Kinesis)
- Knowledge of
data lakes and lakehouse architectures
- Experience with
CI/CD pipelines and DevOps practices
- AWS Certifications (e.g., AWS Certified Data Analytics or Solutions Architect)