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Weekend Amazon Data Engineer Jobs in Toronto, ON

Design and implement data storage solutions using AWS data services such as Amazon RDS, Amazon ... Strong programming skills in languages such as Python, SQL, and Java. Data Modeling and ETL ...

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 ...

Data Architect

Toronto, ON · On-site

$90 - $120/hr

Programming Languages (Python, JavaScript, Kotlin or Java) * Big Data Platforms (Apache Spark, Presto, Amazon EMR) * Cloud Data Warehouses (Snowflake Data Cloud, Google BigQuery, DataBricks Lakehouse ...

... Neo4j, Amazon Neptune) Preferred Qualifications: * Master's degree in Computer Science, Engineering, Data Science, or a related field * Deep expertise designing and implementing semantic layers ...

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Weekend Amazon Data Engineer information

What are Weekend Amazon Data Engineers?

Weekend Amazon Data Engineers are professionals who work with Amazon's data infrastructure, usually on a part-time or flexible basis during weekends. They are responsible for building, maintaining, and optimizing data pipelines and systems that support data analysis and business decision-making. Their work often involves using Amazon Web Services (AWS) tools, programming languages such as Python or SQL, and collaborating with data scientists or analysts. Weekend roles are ideal for those seeking supplementary income, work-life balance, or an opportunity to gain experience in cloud-based data engineering.

What does a typical weekend look like for an Amazon Data Engineer, and how does the work schedule differ from weekday roles?

As a Weekend Amazon Data Engineer, you can expect to focus on monitoring data pipelines, addressing urgent data-related issues, and supporting critical deployments that often occur during lower-traffic periods on weekends. This role may involve collaborating with on-call engineers, data analysts, and product teams to ensure data infrastructure stability and resolve incidents quickly. The weekend schedule typically allows for more independent work, but you will still participate in virtual stand-ups or handoff meetings with weekday teams to maintain continuity. Flexibility and strong communication are important, as you'll often be the primary point of contact for data engineering concerns during your shift.

What are the key skills and qualifications needed to thrive as a Weekend Amazon Data Engineer, and why are they important?

To thrive as a Weekend Amazon Data Engineer, you need strong proficiency in data modeling, SQL, and programming languages such as Python or Java, often backed by a degree in computer science or a related field. Familiarity with AWS services (like Redshift, S3, and Glue), ETL tools, and data warehousing certifications is highly valuable. Excellent problem-solving skills, attention to detail, and effective collaboration are standout soft skills for this role. These competencies ensure the reliable and efficient processing of large datasets, supporting business needs even during off-peak times.

What is the difference between Weekend Amazon Data Engineer vs Weekend Amazon Data Analyst?

AspectWeekend Amazon Data EngineerWeekend Amazon Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentData pipelines, cloud platforms, ETL processesData interpretation, reporting, visualization tools
Employer & Industry UsageAmazon, e-commerce, cloud servicesAmazon, retail, marketing teams

Weekend Amazon Data Engineers focus on building and maintaining data infrastructure, while Data Analysts interpret data and generate reports. Both roles often work in the same environment but serve different functions within Amazon's data ecosystem.

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 job categories do people searching Weekend Amazon Data Engineer jobs in Toronto, ON look for? The top searched job categories for Weekend Amazon Data Engineer jobs in Toronto, ON are:
What cities near Toronto, ON are hiring for Weekend Amazon Data Engineer jobs? Cities near Toronto, ON with the most Weekend Amazon Data Engineer job openings:
Data Engineer

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 27 days ago


GFL Environmental rating

6.8

Company rating: 6.8 out of 10

Based on 170 frontline employees who took The Breakroom Quiz

38th of 75 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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