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AWS DATA ENGINNER

  • Toronto, ON, Canada

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Original job description


AWS Data Engineer

Toronto: Hybrid 4 days a week in office

As a senior technical leader, you will collaborate with architecture, analytics, and business teams to define long-term data strategy, establish engineering best practices, and support enterprise-wide data initiatives.

Key Responsibilities

Lead the design, development, and enhancement of cloud-native data engineering frameworks on AWS.

Architect, build, and optimize end-to-end batch and streaming data pipelines for scalability, reliability, and performance.

Drive experimentation and adoption of new and emerging AWS services to improve platform capabilities and operational efficiency.

Establish data engineering standards, patterns, and best practices for data ingestion, transformation, and storage.

Partner with analytics and product teams to support reporting, analytics, and business objectives.

Own data quality, monitoring, observability, and cost optimization strategies across the data platform.

Provide technical leadership and mentorship to mid-level data engineers.

Participate in architectural reviews and contribute to enterprise-wide data strategy and decision-making.

Required Qualifications

10+ years of experience in Data Engineering or Software Engineering.

4-5 years of dedicated hands-on experience with AWS.

Proven experience designing and implementing large-scale, production-grade data platforms.

Expertise with AWS data services, including:

  • Amazon S3
  • AWS Glue
  • Amazon Redshift
  • Amazon EMR
  • AWS Lambda
  • AWS Step Functions
  • Amazon Kinesis
  • Amazon MSK

Strong programming skills in Python, Scala, or Java.

Deep experience with ETL/ELT frameworks and data pipeline orchestration tools, including Airflow and AWS-native orchestration services.

Strong understanding of data modeling, distributed systems, and performance tuning.

Experience with CI/CD practices and Infrastructure as Code tools such as Terraform, AWS CDK, or CloudFormation.

Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Preferred Qualifications

Experience evaluating and implementing new AWS services through proof-of-concept initiatives.

Exposure to real-time streaming data architectures.

Knowledge of data governance, security, and compliance within cloud environments.

Experience supporting analytics, business intelligence, or machine learning platforms.

Experience working within Agile frameworks.

AWS certifications such as:

  • AWS Certified Data Analytics – Specialty
  • AWS Certified Solutions Architect

Technical Leadership Expectations

Serve as a senior technical leader for AWS data engineering initiatives.

Influence data platform architecture, engineering standards, and best practices.

Guide teams in building scalable, reliable, and cost-effective data solutions.

Promote innovation through the evaluation and adoption of emerging AWS capabilities.

Main Improvements

Improved structure and readability.

Eliminated repetitive language while preserving all original requirements.

Clarified leadership expectations and AWS-specific responsibilities.

Standardized qualification and technology sections for a more market-ready JD.

More about this job

Responsibilities

Lead the design and optimization of scalable AWS data platforms and batch and streaming pipelines, while establishing engineering standards and improving data quality, observability, and cost efficiency. Provide technical leadership and mentorship, collaborate with analytics and business teams, and contribute to architecture reviews and enterprise data strategy.

Requirements

Requires 10+ years of data or software engineering experience, including 4–5 years of hands-on AWS experience and a track record building large-scale production data platforms. Candidates should have strong programming, orchestration, distributed systems, data modeling, performance tuning, CI/CD, and Infrastructure as Code experience; AWS certifications and experience with streaming, governance, analytics, or machine learning are preferred.

Skills

  • AWS Data Engineering
  • Python
  • Scala
  • Java
  • Amazon S3
  • AWS Glue
  • Amazon Redshift
  • Amazon EMR
  • AWS Lambda
  • AWS Step Functions
  • Amazon Kinesis
  • Amazon MSK
  • Apache Airflow
  • ETL/ELT
  • Data Modeling
  • Terraform

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Software
  • Management & Leadership

Keywords

  • AWS
  • Data Engineering
  • Cloud-Native Data Platforms
  • Amazon S3
  • AWS Glue
  • Amazon Redshift
  • Amazon EMR
  • AWS Lambda
  • AWS Step Functions
  • Amazon Kinesis
  • Amazon MSK
  • Python
  • Scala
  • Java
  • ETL/ELT
  • Apache Airflow
  • Data Pipelines
  • Batch Processing
  • Streaming Data
  • Data Modeling
  • Distributed Systems
  • Performance Tuning
  • CI/CD
  • Infrastructure as Code
  • Terraform
  • AWS CDK
  • CloudFormation
  • Data Quality
  • Data Governance
  • Agile

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