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Entry Level Aws Data Engineer Jobs in Toronto, ON

Utilize AWS analytics and data processing services such as AWS Glue, Amazon EMR, and AWS Lambda to ... Strong programming skills in languages such as Python, SQL, and Java. Data Modeling and ETL ...

Senior Data Engineer

Oakville, ON · Hybrid

CA$127K - CA$155K/yr

Help the architect stand up the managed AWS foundation and the layered data zones, from raw through ... Product engineering teams build their own customer-facing data products. Support them so they ...

We are looking for a skilled and detail-oriented Data Engineer to join our growing data team. In ... Familiarity with AWS services, particularly Redshift and Glue, and comfort working in a cloud data ...

We are looking for a skilled and detail-oriented Data Engineer to join our growing data team. In ... Familiarity with AWS services, particularly Redshift and Glue, and comfort working in a cloud data ...

As a Data Engineer at TheAppLabb, you will be responsible for designing, developing, and optimizing ... AWS, GCP, or Azure) and services like S3, Redshift, BigQuery,or Snowflake. · Experience with ...

As a Data Engineer at TheAppLabb, you will be responsible for designing, developing, and optimizing ... Knowledge of Cloud Platforms (AWS, GCP, or Azure) and services like S3, Redshift, BigQuery,or ...

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 ... Experience withbroader cloud platformservicessuch asGCP(Cloud Functions, Pub/Sub, Dataflow), AWS ...

You will collaborate with AI engineers and data scientists to deliver high-quality, data-centric ... Experience deploying data solutions in cloud environments (AWS, Azure, GCP). Familiarity with ...

Data Architect

Oakville, ON · Hybrid

CA$165K - CA$210K/yr

... engineers who can run with them, this is your engagement. What You'll Do * Define a managed AWS ... Specify the layered data model - raw to cleansed to curated to a fully safe analytical layer that ...

... AWS, or GCP). * Experience with big data technologies (e.g., Spark, Kafka) and relational / NoSQL databases is an asset. * Understanding of DevOps and DataOps practices, including CI/CD and ...

New

Solid understanding of q language and time-series data structures. * Experience working in Unix ... Knowledge of Python, cloud platforms (AWS, GCP, Azure), or other time-series databases. * Exposure ...

Data Engineering Consultant

Toronto, ON · On-site

CA$95K - CA$120K/yr

We build solutions across diverse domains - backend, frontend, cloud, mobile, data engineering ... Python, Databricks, PySpark or Spark, SQL, Airflow, Cloud (AWS, GCP, Azure) * Strong communication ...

Data Scientist

Toronto, ON · On-site

CA$80K - CA$120K/yr

The Opportunity Join an exciting team of data scientists and engineers at the forefront of using ... AWS. * Experience with CI/CD pipelines and modern deployment practices. * Exposure to fraud ...

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Entry Level Aws Data Engineer information

What does an entry level AWS data engineer do?

An Entry Level AWS Data Engineer is responsible for helping to design, build, and maintain data pipelines and infrastructure in Amazon Web Services (AWS) environments. They work with data storage tools like Amazon S3, databases such as Amazon RDS or Redshift, and data processing services like AWS Glue or EMR. Their role often involves data extraction, transformation, and loading (ETL), ensuring data is accessible and usable for analytics and business needs. They typically collaborate with data scientists, analysts, and senior engineers while following best practices for cloud security and scalability.

What are the key skills and qualifications needed to thrive as an entry level AWS data engineer?

To thrive as an Entry Level AWS Data Engineer, you need a solid understanding of data structures, SQL, Python or similar programming languages, and a basic grasp of cloud computing concepts, ideally supported by a relevant degree or coursework. Familiarity with AWS services such as S3, Redshift, Glue, and data visualization or ETL tools, along with certifications like AWS Certified Data Analytics – Specialty, is highly valuable. Strong problem-solving abilities, attention to detail, and effective communication skills help you stand out in collaborative, fast-paced environments. These skills and qualifications are crucial for building scalable data solutions, ensuring data quality, and enabling data-driven decision-making for organizations using AWS.

What are some typical projects an entry level AWS data engineer might work on?

As an Entry Level AWS Data Engineer, you may be involved in projects such as building data pipelines, automating data ingestion, or assisting in the migration of on-premises data to AWS cloud services. These projects typically require collaboration with data analysts, senior engineers, and sometimes business stakeholders to ensure that clean, well-structured data is available for reporting and analytics. Your contributions help streamline data flows, improve data quality, and support the team’s ability to make data-driven decisions, providing a strong foundation for future growth and responsibilities.

What is the difference between Entry Level Aws Data Engineer vs Data Analyst?

AspectEntry Level Aws Data EngineerData Analyst
Required CredentialsBasic AWS certifications, SQL, PythonExcel, SQL, basic data visualization tools
Work EnvironmentCloud platforms, data pipelines, ETL processesData interpretation, reporting, dashboards
Industry UsageTech, finance, healthcare with cloud infrastructureBusiness, marketing, finance sectors

While both roles involve working with data, Entry Level Aws Data Engineers focus on building and maintaining cloud-based data pipelines using AWS tools, whereas Data Analysts interpret data and create reports to support business decisions. The roles often overlap in skills like SQL and basic scripting, but differ in their core responsibilities and work environments.

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

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

What are popular job titles related to Entry Level Aws Data Engineer jobs in Toronto, ON?

For Entry Level Aws Data Engineer jobs in Toronto, ON, the most frequently searched job titles are:

Infographic showing various Entry Level Aws Data Engineer job openings in Toronto, ON as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Full-time

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Re-posted 28 days ago


GFL Environmental rating

6.9

Company rating: 6.9 out of 10

Based on 172 frontline employees who took The Breakroom Quiz

45th of 90 rated recycling and waste


Job description


Job Description

Ready to elevate your career? GFL is expanding! We are officially hunting for our next Data Engineer in Vaughan, ON-someone ready to bring fresh ideas and grow alongside a dynamic team.

About Us

GFL is one of the largest diversified environmental services companies in North America, providing comprehensive solid waste management services from its platform of facilities throughout Canada and 18 U.S. states. Recognized by our signature fleet of bright green trucks and equipment, we offer a wide range of environmental and industrial services to businesses, communities and households, providing a consolidated and sophisticated approach to meeting our customers' needs. One of the keys to our success lies in the diversity of our services and our ability to deliver robust integrated solutions, all from a single efficient company. We believe that, by providing safe, accessible and cost-effective solutions, we encourage greater environmental responsibility and allow our customers and the communities we serve to be Green For Life.

The Role

The Data Engineer will be responsible for developing, maintaining, testing, and optimizing data management systems with a focus on Data Lakehouse architecture. The role includes working with vast datasets, designing scalable data models, managing data warehouses and lakes, and ensuring seamless data integration and accessibility for analytics and business intelligence.

Key Responsibilities

Design and Implementation of Data Pipelines: Develop and maintain robust, scalable, and efficient data pipelines that can ingest, process, and distribute data across multiple AWS services and systems.

Data Storage and Database Management: Design and implement data storage solutions using AWS data services such as Amazon RDS, Amazon DynamoDB, Amazon Redshift, and Amazon S3, ensuring data integrity, availability, and security.

Data Processing and Analysis: Utilize AWS analytics and data processing services such as AWS Glue, Amazon EMR, and AWS Lambda to analyze data, derive insights, and support business decision-making.

Data Security and Compliance: Implement and manage security measures to protect data and ensure compliance with data protection regulations and AWS best practices, including encryption, access controls, and audit logging.

Optimization and Scalability: Monitor, optimize, and scale data infrastructure and applications to improve performance, reduce costs, and accommodate growing data volumes.

Collaboration and Support: Work closely with data scientists, business analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs. Provide support for data-related technical issues.

Innovation and Continuous Improvement: Stay abreast of new AWS features and technologies and explore innovative ways to enhance data architecture and operations for better efficiency and effectiveness.

What We're Looking For (Qualifications)

Technical Expertise: Proficient in AWS services relevant to data engineering, such as Amazon S3, Amazon Redshift, AWS Glue, Amazon EMR, and AWS Lambda. Strong programming skills in languages such as Python, SQL, and Java.
Data Modeling and ETL Processes: Experience in data modeling, ETL (Extract, Transform, Load) development, and understanding of data warehousing concepts.
Database Management: Knowledge of database management, performance tuning, and query optimization.
Problem-Solving Skills: Strong analytical and problem-solving abilities, with the capacity to work on complex data systems.
Communication and Collaboration: Excellent communication and teamwork skills, with the ability to work effectively in a collaborative environment.

Education and Experience:
A bachelor's degree in computer science, Engineering, or a related field.
Previous experience as a data engineer or in a similar role, specifically with AWS cloud services.
Desired Certifications:
AWS Certified Data Analytics - Specialty.
AWS Certified Solutions Architect - Associate or Professional.

What We Offer

Why join us? We believe in taking care of our team. Here is a snapshot of our total rewards you can expect:

Health: Comprehensive medical, dental, and vision insurance.

Wellness: Employee Assistance Program, life insurance, and paid time-off

Financial: RRSP matching, profit sharing and competitive wages

Culture: Growth opportunities and continuous learning opportunities

Join us and become part of "Team Green" at GFL Environmental, where your skills and dedication will be valued and rewarded. Apply now for this exciting opportunity!


#GFLTalent


We thank you for your interest. Only those selected for an interview will be contacted.


GFL is committed to equal opportunity for all, without regard to race, religion, color, national origin, citizenship, sex, sexual orientation, gender identity, age, veteran status, disability, genetic information, or any other protected characteristic. If you are interested in applying for employment and need special assistance or an accommodation to apply for a posted position, please contactmyworkdayrecruitment@gflenv.com
Please note that GFL does not provide visa sponsorship
for this position. Valid work authorization in the country where the job is located is required.Successful candidates will be required to provide valid documentation confirming their eligibility to work in the country where the job is located prior to their start date.


This hiring process may utilize machine-based systems to assist in screening and assessing applicants. Final selection decisions are made by our recruitment team.



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