This job post is closed and the position is probably filled. Please do not apply.
🤖 Automatically closed by a robot after apply link
was detected as broken.
Description:
Architect and develop efficient, scalable data pipelines using modern ETL frameworks to transform data from diverse sources into centralized data warehouses or data lakes.
Collaborate with clients to understand and translate their business needs into technical requirements for data infrastructure solutions.
Design, build, and maintain cloud-based data platforms (Azure, AWS, and/or GCP) that enable seamless integration of structured, semi-structured, and unstructured data.
Implement data governance best practices and ensure data quality, security, and compliance with relevant regulations.
Build and optimize data models (dimensional, relational, and NoSQL) that support both batch and real-time analytics needs.
Work with BI developers and data scientists to deliver comprehensive data solutions, including dashboards, machine learning models, and AI-driven insights.
Utilize modern software development practices such as CI/CD pipelines, source code management, and agile methodologies to deliver robust and reliable data solutions.
Requirements:
5+ years of experience in data engineering, with hands-on experience in cloud data services, particularly in Azure, AWS and/or GCP.
Expertise in developing scalable ETL pipelines using tools like Azure Data Factory, AWS Glue, Databricks, or Snowflake.
Experience designing and implementing data lakes and data warehouses to support diverse analytics workloads.
Practical experience with BI tools such as Power BI, Tableau, or Looker, and familiarity with modern data visualization principles.
Strong programming skills in Python, with familiarity in SQL, Spark, or PySpark to handle large datasets.
Understanding of data governance, data quality frameworks, and the ability to implement security and privacy controls around sensitive data.
Experience with DevOps practices such as CI/CD, automation, and infrastructure as code (e.g., Terraform, Ansible).
Familiarity with AI/ML technologies and their application in data engineering projects is a plus.
Proven ability to work with business stakeholders to define data-related business needs and deliver value-driven solutions.
Experience working with SAP Hana is strongly desired.
Benefits:
Professional Development budget and time
Career Mentor to help you grow in your career
RRSP/401K match program
Bonus programs to reward you for your accomplishments
Wellness program to keep you healthy
Opportunities to connect – book clubs, games nights, Special Interest Groups, “Coffee & Code” for our developer friends, Team Meetings, and much more