AWS Data Engineer

company; Greater Toronto Area; Hybrid; CAD 60,000 - 80,000; Full time

Job summary

An established industry player is seeking a skilled Data Engineer to join their dynamic team. In this role, you will design and maintain scalable data pipelines using cutting-edge AWS Data Engineering tools. You will implement ETL processes to transform and load data, ensuring high performance and reliability. Collaborating with data scientists and analysts, you will help deliver solutions that meet business needs. This is an exciting opportunity to work in a light hybrid environment, where your expertise will contribute to innovative data solutions and drive impactful projects forward.

Qualifications

• 3-5 years of experience in data engineering with AWS tools.
• Strong programming skills in Python, Java, or Scala.
• Experience with ETL processes and data warehousing solutions.

Responsibilities

• Design and maintain scalable data pipelines using AWS tools.
• Implement ETL processes for data integration.
• Collaborate with teams to deliver data solutions.

Skills

Data Engineering

AWS Data Engineering tools

ETL processes

Apache Kafka

Python

SQL

Agile Scrum

Test Driven Development (TDD)

Education

Bachelor's degree in Computer Science

Professional certification in AWS Data Engineering

Tools

AWS Glue

Apache Airflow

Amazon Redshift

MS Azure

Job description

This range is provided by company. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

CA$80.00/hr - CA$90.00/hr

Location: Toronto (light hybrid)

Duration: 6mo with very possible extension

Hr/week: 37.5

Requirements:

• 3-5 years of experience in data engineering, with a focus on AWS Data Engineering tools.
• ETL processes and tools (e.g., AWS Glue, PySpark, Apache Airflow).
• Event streaming technologies (e.g., Apache Kafka, AWS Kinesis).
• Strong programming in Python, Java, or Scala.
• SQL and database management systems (e.g., PostgreSQL, MySQL).
• Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
• Experience with Agile Scrum and XP methodologies.
• Experience with Test Driven Development (TDD).
• Bachelor's degree in Computer Science, IT or a related field.
• Professional certification in AWS Data Engineering
• Data warehousing solutions (e.g., Amazon Redshift, Snowflake) - nice to have
• Knowledge of data governance and security best practices - nice to have
• Experience with MS Azure and MS Fabric - nice to have

Responsibilities:

• Design, develop, and maintain scalable data pipelines using AWS Data Engineering tools (e.g., AWS Glue, AWS Lambda, Amazon Redshift).
• Implement ETL processes to extract, transform, and load data from various sources into data warehouses and data lakes.
• Develop and manage event streaming solutions using tools such as Apache Kafka, AWS Kinesis, or similar technologies.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
• Optimize and troubleshoot data pipelines to ensure high performance and reliability.
• Monitor and maintain data quality and integrity across all data systems.
• Stay up-to-date with the latest trends and best practices in data engineering and AWS technologies.
• Work within Agile Scrum and XP methodologies, participating in sprint planning, daily stand-ups, and retrospectives to ensure timely delivery of projects.
• Apply Test Driven Development (TDD) practices to ensure high-quality code and robust data solutions.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Consulting

• Industries

  IT Services and IT Consulting

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