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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
- Bachelors or Masters 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 .
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.