AWS Data Engineer
Location: Toronto
Key Responsibilities
Lead the design, build, and evolution of cloud-native data engineering frameworks on AWS Architect and optimize end-to-end data pipelines (batch and streaming) for performance, reliability, and scalability Drive adoption and experimentation with new and emerging AWS services to improve efficiency and innovation Establish engineering standards, patterns, and best practices for data ingestion, transformation, and storage Collaborate with analysts, and product teams to support analytics Own data quality, monitoring, observability, and cost optimization strategies Provide technical leadership and mentorship to mid-level data engineers Participate in architectural reviews and contribute to enterprise-wide data strategy
Required Qualifications
5+ years of experience in data engineering or software engineering, with strong & dedicated hands-on AWS.
Proven experience designing large-scale, production-grade data platforms Expertise with core AWS data services such as:
Amazon S3, Glue, Redshift, EMR
Lambda, Step Functions
Kinesis / MSK
Strong programming skills in Python, Scala, or Java Deep experience with ETL / ELT frameworks and data pipeline orchestration tools (Airflow, AWS-native equivalents, etc.) Solid knowledge of data modeling, distributed systems, and performance tuning Experience working in CI/CD, Infrastructure as Code (Terraform, CDK, CloudFormation) Strong communication skills with the ability to translate technical concepts for non-technical stakeholders
Preferred Skills
Experience experimenting with or adopting new AWS services and driving proof-of-concepts Exposure to real-time streaming architectures Familiarity with data governance, security, and compliance in cloud environments Experience supporting analytics, BI, or ML platforms Experience with Agile Frameworks AWS certifications (e.g., AWS Certified Data Analytics – Specialty, Solutions Architect)