Technology Data Engineer

Purolator; United States; Remote; USD 80,000 - 110,000; Full time

Job summary

Join a forward-thinking company as a Technology Data Engineer, where your expertise in data engineering will play a pivotal role in building and maintaining robust data infrastructure. This mid-level position emphasizes collaboration with analysts and data scientists to ensure reliable data access and governance. You'll design data pipelines, automate workflows, and implement data governance practices, all while staying current with modern data architecture trends. If you're passionate about data reliability and making a meaningful impact, this is the opportunity for you!

Qualifications

• 3-5 years of experience in data engineering roles in cloud environments.
• Proven expertise with cloud data platforms and data-related services.
• Strong proficiency in SQL, Python, and data processing.

Responsibilities

• Design and optimize data pipelines for efficient data integration.
• Implement ETL/ELT workflows for high-performance data processing.
• Ensure data quality, consistency, and integrity through validation.

Skills

SQL

Python

Data Governance

ETL/ELT

Data Management Concepts

Data Architecture

Problem Solving

Collaboration

Education

Bachelor's or Master’s degree in computer science

Tools

AWS

Azure

Snowflake

Apache Airflow

Terraform

Docker

Kubernetes

Job description

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Technology Data Engineer

Date: 9 May 2025

Location:

Mississauga, ON, CA, L5N 0E1

It’s not a package. It’s a promise.

As Canada’s leading integrated freight, package, and logistics provider, we’ve been helping promises get where they need to be for more than 60 years. How does the magic happen? The journey starts with you. The places we go, the elements we brave, the promises we deliver – it’s all possible because of our people. So, whether you’re looking to build new skills, make an impact in your community, or inspire your team, we go there for you.

Description

The Data Engineer on the Data Management team plays a key role in building and maintaining scalable, secure, and well-governed data infrastructure to support analytics and decision-making. This role helps enable data-driven decision-making by ensuring fast, reliable, and governed data access for business and analytics teams. The Data Engineer is responsible for developing data pipelines, automating data workflows, and ensuring data quality, security, and compliance with governance policies. Success in this role requires a solid understanding of the underlying cloud infrastructure and data architecture to design solutions that are both technically sound and aligned with enterprise standards. The ideal candidate will collaborate with analysts, data scientists, and business stakeholders to enable efficient, trustworthy, and accessible data across the organization.

This role is ideal for a Data Engineer passionate about ensuring data reliability, governance, and security to drive trusted analytics and business insights. This is a mid-level individual contributor role, requiring a strong degree of technical ownership and cross-functional influence.

Responsibilities

• Design, develop, and optimize data pipelines for efficient data integration, storage, and retrieval.
• Implement ETL/ELT workflows to ensure high-performance data transformation and processing.
• Develop and maintain data models to support analytics and reporting needs.
• Automate data workflows, including validation, monitoring, governance enforcement, and CI/CD-based pipeline deployments.
• Develop monitoring, alerting, and logging solutions to ensure observability across data pipelines and infrastructure components.
• Ensure data quality, consistency, and integrity through validation frameworks and anomaly detection.
• Monitor and optimize database performance, storage efficiency, and data processing speed.
• Implement data governance and security at the infrastructure level in compliance with policies and industry regulations.
• Define data engineering standards and best practices and provide guidance on building pipelines and workflows that align with enterprise requirements.
• Evaluate and implement efficient methods for sourcing new datasets from internal or external applications, considering API access, change data capture (CDC), and system architecture.
• Support metadata management, data cataloging, and documentation for transparency and usability, including contributions to master data management to ensure consistency and accuracy of key data assets.
• Collaborate with analytics, IT, and business teams to align data solutions with organizational goals.
• Stay current with modern data architecture trends (e.g. containerization, Lakehouse)

Education

• Bachelor's or Master’s degree in computer science, Data Engineering, Information Systems, or a related field.

Experience

• 3-5 years of experience in data engineering roles in cloud environments.
• Proven hands-on expertise with cloud data platforms (AWS, Azure, Microsoft Fabric, Snowflake) and a broad range of data-related services (e.g., IAM, S3, Glue, Lambda, Redshift, RDS, Athena, Step Functions).
• Strong proficiency in SQL (including Spark SQL), Python (with PySpark), and Scala for data processing and scripting.
• Experience with ETL/ ELT tools (e.g. AWS Glue, Step Functions, Apache Airflow).
• Experience working with big data technologies (Spark, RedShift, Kinesis, Apache Iceberg, Kafka).
• Experience working with NoSQL databases (DynamoDB, MongoDB)
• Experience managing cloud infrastructure with IaC tools (e.g., Terraform Enterprise, CloudFormation), container orchestration (e.g., Docker, Kubernetes) and workflow orchestration tools (e.g., AWS Step Functions, Apache Airflow).
• Experience designing and implementing CI/CD pipelines for data engineering workflows using tools like Git, GitHub Action and SonarQube.
• Understanding of data architecture and cloud infrastructure principles to support modern data solutions.
• Solid understanding of cloud monitoring and logging tools (e.g. CloudWatch), data security, access control, and governance principles.
• Strong problem-solving, communication, and collaboration skills across technical and business teams in a fast-paced environment.

Preferred Experience

• Comfortable providing technical guidance, documentation, and mentorship to peers and stakeholders to promote data engineering best practices.
• Hands-on experience with metadata management, data governance, and master data management (MDM) platforms (e.g., Collibra, Atlan, Informatica MDM).

Skills

Network Design

Robotic Application Development

Data Management Concepts

Data Standards and Procedures

Data Governance

POSTING DETAILS
Location: 530 - Corporate
Working Conditions: Office Environment

Reports to: Senior Manager Technology Data Management and Governance
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Purolator is an equal opportunity employer committed to diversity and inclusion. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, Aboriginal/Indigenous status or any other factors considered discriminatory. If you require an accommodation during the recruitment process, we will work with you to meet your needs.

We recognize that our employees and their families are key stakeholders. We will only be successful as a business if we provide our employees with a safe and healthy workplace and we have the right people in the right roles with the support they need to succeed. We hire for attitude and train for skills. To learn more about us and our values, go to www.purolator.com.

At Purolator, every day is an opportunity for our employees to connect with one another and with our customers to help make a positive impact in the communities where we live, work and play.

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