Google Cloud Data Engineer - Scalable Pipelines & ML

TechBlocks; Vaughan; On-site; CAD 90,000 - 130,000; Full time

Job summary

TechBlocks is seeking a Data Engineer to design and develop scalable data pipelines on Google Cloud, enabling reliable data processing and ML model integration. You will collaborate with data scientists and engineers to expand the enterprise data platform, ensuring high performance and reliability in a modern cloud-based environment.

The role requires 10+ years in data engineering, strong Python/Big Data tech, and experience in agile environments with CI/CD.

Qualifications

• 10+ years of experience in Big Data and Data Engineering for enterprise-level apps in public cloud (prefer Google Cloud).
• Experience building cloud-native data pipelines with Python, Airflow, Spark, and Beam.
• Strong SQL and data warehousing knowledge (PostgreSQL, BigQuery).
• Knowledge of MongoDB and AlloyDB is a plus.
• Experience with CI/CD tools (Azure DevOps or similar), Git.
• Experience with TDD, Agile development, and collaborating in cross-functional teams.
• Excellent communication with technical and non-technical stakeholders.
• Bachelor's degree in CS or related engineering, or equivalent experience.
• Optional: Docker image builds and production deployments; Kubernetes pods & Deployments with Terraform.
• Optional: C#, .NET Core, and microservices exposure.

Responsibilities

• Use the latest technology to build data pipelines and integrate machine learning models.
• Build and expand our data platform.
• Develop applications that run on Google Cloud-based infrastructure.

Skills

Python

Airflow

Spark

Beam

SQL

BigQuery

PostgreSQL

Cloud

CI/CD

Git

Kubernetes

Docker

Terraform

Agile

TDD

Communication

Data pipelines

Education

Bachelor's degree in Computer Science

Tools

Google Cloud Platform

MongoDB

AlloyDB

Docker

Terraform

Job description

TechBlocks is seeking a Data Engineer to design and develop scalable data pipelines on Google Cloud, enabling reliable data processing and ML model integration. You will collaborate with data scientists and engineers to expand the enterprise data platform, ensuring high performance and reliability in a modern cloud-based environment.

The role requires 10+ years in data engineering, strong Python/Big Data tech, and experience in agile environments with CI/CD.