Principal Data Engineer

Role: Principal Data Engineer

Location: Toronto, ON

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)