AI Data Engineer

Definity; Waterloo; Hybrid; CAD 80,000 - 120,000; Full time

Job summary

A leading company in the insurance sector is seeking an AI Data Engineer to bridge data science and engineering. This role focuses on developing and deploying data assets for AI applications. Responsibilities include building data infrastructure and collaborating with teams to optimize data processes. The ideal candidate will have strong programming skills, experience with Big Data tools, and a background in machine learning.

Benefits

Hybrid work

Share ownership

Pension

Educational resources

Wellness programs

Qualifications

• 5+ years in technology and data engineering roles.
• 3+ years of cloud experience.
• Experience with machine learning and AI applications.

Responsibilities

• Design and implement robust data pipelines for large data volumes.
• Collaborate with Data Scientists and ML Engineers to integrate AI solutions.
• Continuously improve data processing and model inference efficiency.

Skills

Python

Java

Scala

Problem-solving

Education

Bachelor's or master’s degree in Computer Science

Degree in Data Science

Tools

BigQuery

Hive

Databricks

TensorFlow

PyTorch

Vertex AI

Apache Airflow

Docker

Kubernetes

Google Cloud Platform

Job description

Join to apply for the AI Data Engineer role at Definity .

Company Overview

Definity is the parent company to some of Canada’s most long-standing and innovative insurance brands, including Economical Insurance, Sonnet Insurance, Family Insurance Solutions, and Petline Insurance. Our ambition is to be one of Canada’s leading and most innovative property and casualty insurers. We foster a culture that’s collaborative, ambitious, rewarding, and empowering.

We offer a flexible, hybrid work experience where employees work from the office and virtually, depending on their work and team needs. Join us and bring your true self along.

Role Summary

The AI Data Engineer is a pivotal role that bridges data science and engineering, focusing on developing and deploying data assets with integrated models. Responsibilities include building and maintaining data infrastructure and pipelines that support AI and machine learning applications. You will work with advanced tools and platforms to transform and optimize data processes.

Key Responsibilities

• Data Ingestion and Processing : Design and implement robust data pipelines for large data volumes from diverse sources.
• Data Preparation : Preprocess and transform data for machine learning algorithms.
• Feature Engineering : Develop and select features to enhance model performance.
• Data Support for Models : Collaborate with Data Scientists and ML Engineers to integrate AI solutions, optimizing for large data volumes.
• Scalability : Design scalable data architectures for growing AI demands.
• Performance Optimization : Continuously improve data processing and model inference efficiency.

Required Skills

• Strong programming skills in Python, Java, or Scala.
• Experience with Big Data tools (BigQuery, Hive), data processing, and ETL tools like Databricks.
• Expertise with GCP cloud environment.
• Familiarity with ML frameworks like TensorFlow, PyTorch, Vertex AI.
• Understanding of data modeling and database design.
• Experience with data pipeline orchestration tools like Apache Airflow.
• Problem-solving skills for complex data engineering challenges.

Qualifications

• Bachelor's or master’s degree in Computer Science, Data Science, or related field.
• Experience with machine learning and AI applications.
• 5+ years in technology and data engineering roles.
• 3+ years of cloud experience.

Desired Skills

• Experience with MLOps practices.
• Knowledge of Docker, Kubernetes.
• Strong communication and collaboration skills.
• Experience with Google Cloud Platform.
• Understanding of AI models.

Additional Information

We encourage applicants who don't meet all requirements; diversity and inclusion are vital to our success. Benefits include hybrid work, share ownership, pension, educational resources, wellness programs, and more. Compensation varies based on location, skills, and experience. Background checks are required.

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