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Senior Amazon Data Engineer Jobs in Toronto, ON (NOW HIRING)

ShyftLabs

Senior Data Engineer

Toronto, ON

The Opportunity ShyftLabs is seeking an experienced Senior / Lead Data Engineer to lead the design, architecture, and delivery of enterprise-scale data platforms for Fortune 500 organizations. This ...

Rockstar

Senior Data Engineer

Toronto, ON

A Sr. Data Engineer is sought to join the team. This individual will play a key role in evolving the core data platform, which includes data pipelines, machine learning models, and various databases.

Konrad

Senior Data Engineer

Toronto, ON · Hybrid

CA$120K - CA$145K/yr

About The Role As a Senior Data Engineer you'll be tasked with designing, building, and maintaining scalable data platforms and pipelines. Your deep knowledge of data platforms such as Azure Fabric ...

Vangard, Inc.

Sr Data Engineer, Specialist

Toronto, ON · On-site

CA$90K - CA$140K/yr

We are looking for a Sr Data Engineer with in-depth expertise in AWS, Databricks, and modern data architecture and data modeling to help build the next generation of our data foundation , including ...

New

Dentsu Aegis Network

Data Engineer

Toronto, ON

CA$70K - CA$80K/yr

We'relooking for a Data Engineer with3-5years of hands-on experience to join our team.You'llown the ... Meta Advanced Analytics, Amazon Marketing Cloud). * Experience withbroader cloud ...

Citi

Data Engineer

Mississauga, ON

The Applications Development Technology Lead Analyst is a senior level position responsible for ... The Data Engineering Lead will drive the design and implementation of high-throughput data ...

MPA Recruitment

Data Engineer

Toronto, ON · On-site

As a Senior Data Engineer, you will be responsible or designing and developing data processing and data persistence software components for solutions which handle data at scale. Working in agile ...

Morningstar, Inc.

Senior Data Engineer

Toronto, ON · On-site

CA$90K - CA$132K/yr

We are looking for a Senior Data Engineer with a minimum of 5+ years of experience in designing and implementing scalable, end-to-end data engineering solutions. The ideal candidate should have ...

Scotiabank

Senior Data Engineer

Toronto, ON · On-site

We are seeking an experienced Senior Data Engineer with deep expertise in Google Cloud Platform (GCP) to join our growing team. In this role, you will be responsible for designing, building, and ...

GFL Environmental

Senior Data Engineer

Vaughan, ON · On-site

Our GFL team is expanding, and we are seeking a highly skilled Senior Data Engineer with experience in designing and maintaining real-time data streaming pipelines and building robust data lake ...

JLL

Data Engineer 2

Toronto, ON · On-site

We are seeking a Data Engineer P2 who is a self-starter to work in a diverse and fast-paced ... Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) Proficiency in object ...

McKesson

Senior / Lead Data Engineer

Mississauga, ON · On-site +1

Senior/Lead Data Engineer Current Need: The Senior / Lead Data Engineer will bepart of McKesson Decision Intelligence team, and responsibilities include managing data exploration and analysis ...

McKesson

Senior / Lead Data Engineer

Mississauga, ON · On-site +1

Senior/Lead Data Engineer Current Need: The Senior / Lead Data Engineer will bepart of McKesson Decision Intelligence team, and responsibilities include managing data exploration and analysis ...

Ci

Senior Data Engineer

Toronto, ON · On-site

CA$69K - CA$119K/yr

We are currently seeking a Senior Data Engineer to join the Data, AI & Analytics (DNA) Team. A successful data engineering candidate will demonstrates a deep understanding of database concepts, data ...

dentalcorp

Associate Data Engineer

Toronto, ON · On-site

Work with senior team members to troubleshoot data issues, investigate pipeline failures, and document resolution steps. * Contribute to the improvement of repeatable data engineering patterns ...

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Senior Amazon Data Engineer information

What does a senior Amazon data engineer do?

A Senior Amazon Data Engineer is responsible for designing, building, and maintaining large-scale data processing systems on Amazon Web Services (AWS) infrastructure. They work with big data technologies, such as Amazon Redshift, AWS Glue, and Amazon S3, to ensure data is efficiently collected, stored, and made accessible for analytics and business intelligence. Additionally, they often lead data engineering teams, optimize data pipelines for performance, and ensure data quality and security standards are met.

What are some common challenges faced by senior Amazon data engineers when working with large-scale datasets?

Senior Amazon Data Engineers often encounter challenges related to optimizing the performance of data pipelines and ensuring data quality at scale. Managing and transforming massive volumes of data requires expertise in distributed systems, efficient data modeling, and automating data validation processes. Additionally, collaborating with cross-functional teams—such as data scientists, analysts, and software engineers—means balancing differing requirements and priorities while maintaining robust, scalable solutions. Staying current with evolving AWS services and best practices is also essential to address these challenges effectively.

What are the key skills and qualifications needed to thrive as a senior Amazon data engineer, and why are they important?

To thrive as a Senior Amazon Data Engineer, you need advanced proficiency in data modeling, ETL development, SQL, and experience with large-scale data architectures, typically supported by a computer science degree or equivalent. Expertise in AWS services (such as Redshift, S3, Glue), programming languages like Python or Java, and relevant certifications (e.g., AWS Certified Data Analytics) are commonly required. Strong problem-solving abilities, effective communication, and leadership skills distinguish top performers in this role. These skills ensure the efficient design, implementation, and optimization of complex data solutions that drive business insights and support organizational goals.

What is the difference between Senior Amazon Data Engineer vs Amazon Data Engineer?

AspectSenior Amazon Data EngineerAmazon Data Engineer
Required CredentialsTypically requires 5+ years experience, advanced SQL, AWS certificationsEntry to mid-level, foundational SQL, AWS certifications beneficial
Work EnvironmentDesigning complex data pipelines, mentoring, strategic projectsBuilding and maintaining data pipelines, data analysis
Employer & Industry UsageUsed in large-scale data teams within Amazon and similar tech companiesCommon in tech companies, e-commerce, and cloud service providers

The main difference between a Senior Amazon Data Engineer and an Amazon Data Engineer lies in experience, responsibilities, and project complexity. Senior roles involve strategic planning, mentoring, and handling complex data systems, while entry-level roles focus on building and maintaining data pipelines. Both roles require AWS knowledge and data engineering skills, but senior positions demand more experience and leadership capabilities.

What are the most commonly searched types of Amazon Data Engineer jobs in Toronto, ON?

The most popular types of Amazon Data Engineer jobs in Toronto, ON are:

What are popular job titles related to Senior Amazon Data Engineer jobs in Toronto, ON?

For Senior Amazon Data Engineer jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Senior Amazon Data Engineer jobs in Toronto, ON look for?

The top searched job categories for Senior Amazon Data Engineer jobs in Toronto, ON are:

Senior Amazon Data Engineer jobs near you
Infographic showing various Senior Amazon Data Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

Senior Data Engineer

ShyftLabs

Toronto, ON

Full-time

Medical, Dental, Vision

Re-posted 9 days ago

Job description

About ShyftLabs
At ShyftLabs, we live and breathe data. Since 2020, we've been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact. We're growing fast, and we're looking for passionate technical leaders who are excited to solve complex data challenges, build modern cloud platforms, and deliver innovative solutions for enterprise clients. 
 
The Opportunity
ShyftLabs is seeking an experienced Senior / Lead Data Engineer to lead the design, architecture, and delivery of enterprise-scale data platforms for Fortune 500 organizations. This is a highly client-facing leadership role responsible for owning projects from discovery through production deployment. You'll partner directly with client stakeholders to understand business objectives, define technical strategy, architect scalable cloud solutions, and lead engineering teams through successful delivery. The ideal candidate combines deep hands-on expertise with Databricks, Apache Spark, Python, SQL, and modern cloud platforms with proven experience leading complex data modernization initiatives. You'll play a key role in shaping technical direction, mentoring engineers, establishing engineering best practices, and delivering scalable data products that enable analytics, AI, and machine learning.
What You'll Be Doing
Technical Leadership
  • Lead the architecture, design, and implementation of enterprise-scale data platforms from project inception through production deployment.
  • Own technical delivery across multiple client engagements while ensuring high-quality engineering standards.
  • Define solution architecture, technical roadmaps, and implementation strategies aligned with client business goals. 
  • Conduct architecture reviews, code reviews, and establish engineering best practices across project teams.
  • Mentor and coach Data Engineers while fostering technical excellence and continuous learning.
  • Serve as the primary technical leader for complex engineering initiatives and critical project decisions.
Client Partnership
  • Partner directly with Fortune 500 clients to understand business requirements and translate them into scalable technical solutions.
  • Lead discovery workshops, architecture sessions, and technical planning meetings with both business and engineering stakeholders.
  • Present solution designs, delivery plans, and architectural recommendations to technical leadership and executive audiences.
  • Build trusted relationships with client teams while providing technical guidance throughout project execution.
  • Support pre-sales activities by contributing technical expertise, solution estimates, and implementation approaches when required.
Data Engineering & Platform Development
  • Design, develop, and optimize enterprise-grade data pipelines using the Databricks Unified Analytics Platform.
  • Build scalable ETL and ELT frameworks capable of processing large-scale structured and unstructured datasets.
  • Design and implement Lakehouse architectures using Delta Lake and Medallion design patterns.
  • Develop high-performance Spark applications for batch and real-time data processing.
  • Integrate data from enterprise applications, APIs, streaming platforms, and cloud storage solutions.
  • Ensure data quality, integrity, and reliability through automated validation, testing, and monitoring.
Cloud & DevOps
  • Architect cloud-native data platforms across AWS, Azure, or Google Cloud Platform.
  • Implement Infrastructure-as-Code using Terraform or similar technologies.
  • Build and maintain CI/CD pipelines supporting automated testing and deployment.
  • Optimize cloud infrastructure for scalability, reliability, security, and cost efficiency.
  • Monitor platform performance and proactively resolve operational issues.
Data Governance & Security
  • Implement enterprise data governance frameworks and security best practices.
  • Configure Unity Catalog, metadata management, lineage, and role-based access controls.
  • Ensure compliance with organizational security standards and regulatory requirements.
  • Promote data observability and operational excellence across production environments
Cross-Functional Collaboration
  • Partner closely with Product Managers, Data Scientists, Analytics Engineers, Machine Learning Engineers, and Software Engineers to deliver high-impact data products.
  • Enable AI and machine learning initiatives through scalable feature engineering pipelines and production-ready datasets.
  • Contribute reusable frameworks, accelerators, and engineering standards that improve delivery across client engagements.
What You'll Bring
  • Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, or a related technical discipline.
  • 8+ years of experience designing and building enterprise-scale data platforms.
  • 5+ years of hands-on experience with Databricks and Apache Spark.
  • Proven experience leading enterprise data engineering projects from architecture through production delivery.
  • Strong expertise in Python, SQL, and Spark for large-scale data processing.
  • Deep understanding of Delta Lake, Lakehouse architecture, and modern data platform design.
  • Experience working with AWS, Azure, or Google Cloud Platform.
  • Strong knowledge of ETL/ELT frameworks, distributed computing, and data modeling.
  • Experience implementing CI/CD pipelines and Infrastructure-as-Code.
  • Strong understanding of data governance, security, metadata management, and data quality practices.
  • Experience optimizing distributed data processing workloads for performance and cost.
  • Excellent communication and stakeholder management skills with experience working directly with enterprise clients. 
  • Demonstrated ability to mentor engineers and lead technical initiatives
Nice to Have
  • Databricks Certified Professional Data Engineer certification.
  • Experience with Delta Live Tables, MLflow, Unity Catalog, and Databricks SQL.
  • Experience with Kafka, Kinesis, Event Hubs, or other streaming technologies.
  • Hands-on experience with Snowflake, dbt, Airflow, or modern data orchestration tools.
  • Experience with Kubernetes, Docker, and Terraform. 
  • Knowledge of AI/ML data platforms, Feature Stores, or Retrieval-Augmented Generation (RAG) architectures.
  • Previous consulting or professional services experience delivering solutions for enterprise clients.
  • Experience within retail, e-commerce, financial services, logistics, healthcare, or ad-tech environments.
Salary Range
  • $140,000 - $180,000 (CAD)
Why You'll Love Working at ShyftLabs
Lead Enterprise Transformations: Design and deliver modern data platforms that power analytics, AI, and digital transformation initiatives for Fortune 500 organizations.
Technical Ownership: Drive architecture decisions, influence technical strategy, and lead projects from discovery through production.
Growth & Leadership: Mentor talented engineers, shape engineering best practices, and continue developing your technical and leadership skills. 
Hybrid Flexibility: Work three days per week from our downtown Toronto office.
Comprehensive Benefits: 100% employer-paid health, dental, and vision coverage for you and your dependents from day one, along with ongoing learning and professional development opportunities.
 
Inclusion at ShyftLabs
We're building something big, and we want you on the journey with us. If you're ready to solve complex data challenges, lead enterprise projects, and build innovative solutions that create measurable business impact, we'd love to hear from you. ShyftLabs is an equal opportunity employer committed to creating a safe, diverse, and inclusive workplace. We encourage applicants of all backgrounds, including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, and nationality, to apply. If you require accommodation during the interview process, please let us know and we'll be happy to support you.
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