Junior Data Engineer

HRB; Vaughan; On-site; CAD 55,000 - 75,000; Full time

Job summary

HRB in Vaughan, Canada, seeks a Junior Data Engineer to join our data team and help build scalable pipelines powering eco-focused solutions.

As a fresh Computer Science graduate, you will design, implement, and maintain batch and streaming ETL processes using Python, PySpark, AWS, and SQL. This role offers mentorship from senior engineers and exposure to cloud infrastructure and data governance practices.

Qualifications

• Bachelor's degree in Computer Science or related field completed within the last 0–12 months.
• Strong Python foundation and software engineering principles (OOP, data structures, algorithms, Git).
• Experience with Apache Spark / PySpark to process large datasets.
• Working knowledge of AWS core services (S3, EC2, IAM, Lambda).
• Solid grasp of SQL, data modeling concepts, and schema design.

Responsibilities

• Design, build, and maintain automated batch and real-time ETL/ELT pipelines for large-scale environmental data.
• Use Python and PySpark to process structured and unstructured data efficiently.
• Help manage and expand cloud data infrastructure using AWS services (S3, Glue, EMR, Redshift, Lambda).
• Implement automated testing, validation, and monitoring for data quality and governance.
• Collaborate with Data Scientists, Analysts, and Sustainability Specialists to deliver clean data for reporting and ML.

Skills

Python

Apache Spark

PySpark

Git

OOP

Data structures

Algorithms

SQL

Education

Bachelor's degree in Computer Science or related field

Tools

AWS core services (S3, Glue, EMR, Redshift, Lambda)

Job description

We are dedicated to building a cleaner, more sustainable future. By applying innovative technology and data-driven insights to green environmental initiatives, we help measure, analyze, and reduce environmental impact at scale. We are looking for a passionate, forward-thinkingJunior Data Engineerto join our data team and help build the data pipelines powering our eco-focused solutions.

Position Overview

As a fresh graduate joining our team, you will work closely with senior data engineers and analysts to design, build, and maintain high-volume data pipelines. You will transform raw environmental datasets—such as energy metrics, carbon emissions data, and resource usage—into actionable insights. This role is ideal for a recent Computer Science graduate eager to apply modern data tooling (AWS, PySpark, Python) toward solving meaningful sustainability challenges.

Key Responsibilities

Pipeline Development:Design, build, and maintain automated batch and real-time ETL/ELT pipelines to ingest, clean, and transform large-scale environmental data.

Data Processing:Utilize Python and Apache Spark (PySpark) to process structured and unstructured datasets efficiently.

Cloud Infrastructure:Help manage and expand our cloud data infrastructure using core AWS services (e.g., S3, Glue, EMR, Redshift, Lambda).

Data Quality & Governance:Implement automated testing, validation, and monitoring to ensure data accuracy, reliability, and security.

Cross-Functional Collaboration:Partner with Data Scientists, Business Analysts, and Sustainability Specialists to deliver clean, structured data for reporting and machine learning applications.

Required Qualifications

Education:Bachelor’s degree inComputer Science(or a closely related core computing field, such as Computer Engineering or Software Engineering) completed within the last 0–12 months.

Core Programming:Strong foundation inPythonand fundamental software engineering principles (OOP, data structures, algorithms, version control with Git).

Distributed Computing:Academic or hands-on project experience usingApache Spark / PySparkto process large datasets.

Cloud Fundamentals:Working knowledge or project experience withAWScore services (S3, EC2, IAM, Lambda, or managed data services).

Databases & SQL:Solid grasp of relational databases, SQL query writing, data modeling concepts, and basic schema design.

Nice-to-Have / Preferred Qualifications

Coursework, internship, or personal project focus on environmental data, sustainability, clean energy, or IoT telemetry data.

Exposure to workflow orchestration tools (e.g., Apache Airflow, Dagster).

Familiarity with containerization technologies (Docker, Kubernetes).

Knowledge of CI/CD practices for data infrastructure.

What We Offer

Mission-Driven Impact:Direct involvement in projects that combat climate change and advance sustainable practices.

Mentorship & Growth:A collaborative environment with dedicated mentorship from experienced senior data engineers.