Junior Data Engineer
hireVouch · Vaughan, Ontario ·
- Seniority
- Junior
- Employment
- Internship
- Category
- Data engineering
hireVouch · Vaughan, Ontario ·
HRB · Vaughan, Canada
Elsevier · London Wall
Communicate Recruitment · Stellenbosch, South Africa
Jobtailor · Philippines
The Junior Data Engineer will design and maintain ETL pipelines to process environmental data using Python, PySpark, and AWS. This role involves collaborating with senior engineers to support sustainability initiatives through data-driven insights.
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-thinking Junior Data Engineer to join our data team and help build the data pipelines powering our eco-focused solutions.
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.
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.
Education: Bachelor’s degree in Computer 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 in Python and fundamental software engineering principles (OOP, data structures, algorithms, version control with Git).
Distributed Computing: Academic or hands-on project experience using Apache Spark / PySpark to process large datasets.
Cloud Fundamentals: Working knowledge or project experience with AWS core 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.
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.
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.
Capgemini