Role: Principal Data Engineer
Location: Toronto- Hybrid 2 days in office
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
10+ years of experience in data engineering or software engineering, with strong & dedicated hands-on AWS experience of 4-5 years.
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)