Principle Data Engineer
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Job Location:
Monthly Salary:
Posted on:
2 days ago
Vacancies:
1 Vacancy
Job Summary
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)
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)
