AWS DATA ENGINNER

Toronto, ON
Hybrid
Posted Oct 7, 2026
1 position

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Employment type: Contract
Experience level: Lead · 10+ years
Posting language: English
Working hours: 40 hours per week
Office presence: 4 days per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

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.

Job details

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.

What you’ll do

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.