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Jobright.ai

Data Engineer (Early Career) (Canada)

Canada

Job type: Full-time
Experience: Recent graduate or early-career professional (0–2 years of experience) with a degree in Computer Science, Data Engineering, or a related technical field
Posting language: English
Posted: Sep 27, 2026

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Original job description

Jobright is your personal AI job search agent transforming the job search process. They are seeking an early-career Data Engineer to design and build data pipelines, ensuring data quality and collaborating with analytics and product teams.

Why Join Us

Build real, production AI agents used by real users

High ownership and impact

Work at the intersection of AI, agents, and product

Shape how people experience AI-driven job search

Responsibilities

Design and build reliable data pipelines that move data from diverse sources into centralized warehouses and lakes for downstream consumption

Own the full lifecycle of ETL/ELT processes, from schema design and ingestion to transformation, testing, and deployment

Ensure data quality and consistency by implementing validation checks, anomaly detection, and automated alerting across critical pipelines

Partner with analytics, data science, and product teams to understand their data needs and deliver clean, well-documented datasets

Optimize query performance, storage costs, and pipeline reliability as data volumes and complexity grow

Qualification

Required

Recent graduate or early-career professional (0–2 years of experience) with a degree in Computer Science, Data Engineering, or a related technical field

Strong proficiency in Python and SQL, with hands-on experience writing and debugging data transformation logic

Practical understanding of data modeling, warehouse design patterns, and the trade-offs between batch and streaming architectures

Solid software engineering foundations, including comfort with APIs, version control (Git), and writing testable, production-ready code

Preferred

Previous internship or project experience building end-to-end data pipelines or managing datasets at non-trivial scale

Familiarity with cloud data platforms such as Snowflake, BigQuery, Redshift, or Databricks

Hands-on exposure to orchestration tools like Airflow, dbt, or Prefect, and streaming technologies like Kafka or Spark Streaming

Curiosity about how data powers product decisions, and a willingness to dig into messy, ambiguous data problems

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More about this job

Responsibilities

Design, build, and manage reliable data pipelines and ETL/ELT processes, including ingestion, transformation, testing, and deployment. Maintain data quality and pipeline reliability, optimize performance and storage costs, and collaborate with analytics, data science, and product teams to deliver well-documented datasets.

Requirements

Applicants should be recent graduates or early-career professionals with 0–2 years of experience and a degree in Computer Science, Data Engineering, or a related technical field. Required qualifications include strong Python and SQL skills, knowledge of data modeling and batch versus streaming architectures, and software engineering experience with APIs, Git, and testable production-ready code; cloud platforms and orchestration or streaming tools are preferred.

Skills

Python
SQL
Data Pipeline Development
ETL/ELT
Data Modeling
Data Warehousing
Data Quality
Data Validation
Anomaly Detection
Query Optimization
Git
API Integration
Software Testing
Cloud Data Platforms
Workflow Orchestration
Streaming Data

Benefits

High Ownership and Impact
Opportunity to Build Production AI Agents
Opportunity to Shape AI-Driven Job Search

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Data Engineering
Data Pipelines
ETL
ELT
Data Ingestion
Data Transformation
Data Modeling
Data Warehouses
Data Lakes
Data Quality
Data Validation
Anomaly Detection
Automated Alerting
Batch Processing
Streaming Architectures
APIs
Git
Snowflake
BigQuery
Redshift
Databricks
Airflow
dbt
Prefect
Kafka
Spark Streaming
Query Optimization
Software Engineering

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