Position Description:
This role is hybrid and requires you to be at our client's and/or downtown Toronto office at a minimum 2 days per week - subject to change at any time.
We are seeking a skilled Databricks Developer to design, develop, and optimize scalable data solutions on the Databricks platform. The ideal candidate will be responsible for building and managing database schemas, developing procedures for Operational Data Store (ODS) environments using Databricks Delta Lake tables, and ensuring efficient data archiving and document indexing processes. The role requires strong expertise in data engineering, cloud-based analytics platforms, and data lifecycle management.
Your future duties and responsibilities:
. Design and develop database schemas and procedures for Operational Data Store (ODS) using Databricks Delta Lake tables.
. Build and maintain scalable ETL/ELT pipelines within the Databricks ecosystem.
. Define and implement data contracts for data archiving and document indexing processes.
. Ensure efficient and reliable data archiving, retention, and retrieval mechanisms.
. Develop and optimize document indexing strategies to improve data accessibility and search performance.
. Collaborate with business analysts, architects, and data teams to understand data requirements and translate them into technical solutions.
. Monitor and optimize data processing performance, storage efficiency, and query execution.
. Implement data quality, governance, and security standards across data platforms.
. Support troubleshooting, performance tuning, and production issue resolution.
. Maintain technical documentation for data models, workflows, and integration processes.
Required qualifications to be successful in this role:
• Strong 5+ years of experience with Databricks and Apache Spark
• Expertise in Delta Lake architecture, including table design, optimization, and management
• Proficiency in SQL and PySpark / Scala for building data engineering solutions
• Experience designing and implementing enterprise-grade database schemas
• Knowledge of data lifecycle management, including archiving and retention strategies
• Understanding of data contracts, metadata management, and data governance principles
• Experience with cloud platforms such as Azure, AWS, or GCP
• Familiarity with ETL/ELT frameworks and data pipeline orchestration tools
• Strong analytical thinking, troubleshooting, and performance optimization skills
Preferred Qualifications
• Experience working on large-scale enterprise data platforms
• Knowledge of document management and indexing systems
• Exposure to CI/CD pipelines and DevOps practices for data engineering
• Databricks certification is an added advantage
Education & Experience
• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field
• 5+ years of experience in Databricks / Data Engineering development roles
"CGI is providing a reasonable estimate of the pay range for this role. The determination of this range includes factors such as skill set level, geographic market, experience and training, and licenses and certifications. Compensation decisions depend on the facts and circumstances of each case. A reasonable estimate of the current range is $95,–$,. This role is an existing vacancy."
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Skills:
Databrick Developer • Toronto, Canada
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