Senior Data Engineer, Growth & Personalization (Hybrid, Toronto)

HelloFresh; Toronto; Hybrid; CAD 170,000 - 180,000; Full time

Benefits offered by this job

Box Discount

Health & Wellness benefits

RRSP Matching

Vacation & PTO

Family Benefits

Growth & Development

Work Hard & Have Fun

Diversity & Inclusion Initiatives

Flexible Hybrid work

Job summary

HelloFresh is seeking a Senior Data Engineer for a hybrid role at our Toronto headquarters. You will own end-to-end data pipelines, partner with Data Scientists, ML Engineers, and BI teams, and help advance pricing optimization and customer-value initiatives across the Growth Alliance.

You’ll work with PySpark, AWS, Kubernetes, Kafka and Databricks, applying best practices in data modeling, CI/CD, and testing. Strong collaboration and a product-minded attitude are essential.

Qualifications

• Solid data engineering experience with Python and SQL
• Hands-on experience with PySpark, Kubernetes and Kafka
• Expertise in data modeling, PostgreSQL, AWS S3 and Databricks
• Proven ability to design maintainable data pipelines and CI/CD practices

Responsibilities

• Take ownership of end-to-end data pipelines: architecture, design, development, deployment and operations
• Collaborate with cross-functional teams including Data Scientists, ML Engineers, Product Owners and BI
• Mentor colleagues and act as ambassador for data solutions across HelloFresh platforms
• Leverage modern tooling (Airflow/Prefect, AWS, Databricks) and AI-assisted productivity tools

Skills

Python

SQL

PySpark

Kubernetes

Kafka

PostgreSQL

AWS S3

Databricks

Data Modeling

Data Pipelines

Tools

Airflow

Prefect

Tecton

Databricks

Job description

HelloFresh is seeking a Senior Data Engineer for a hybrid role at our Toronto headquarters. You will own end-to-end data pipelines, partner with Data Scientists, ML Engineers, and BI teams, and help advance pricing optimization and customer-value initiatives across the Growth Alliance.

You’ll work with PySpark, AWS, Kubernetes, Kafka and Databricks, applying best practices in data modeling, CI/CD, and testing. Strong collaboration and a product-minded attitude are essential.