Job Title: Data Engineer – Databricks
Location: Toronto Downtown, ON- Hybrid Onsite
Work Model: Hybrid – 3 days onsite per week
Duration: Long term Contract
Job Description: We are looking for a Data Engineer with strong Databricks experience to design, build, and optimize scalable data pipelines and analytics solutions. The ideal candidate will work closely with data scientists, analysts, and business stakeholders to deliver reliable, high-performance data platforms in a cloud environment.
Key Responsibilities
• Design, develop, and maintain scalable data pipelines using Databricks (Spark/Delta Lake)
• Build and optimize ETL/ELT workflows for large-scale structured and unstructured data
• Develop data transformations using PySpark / Spark SQL
• Integrate data from multiple sources including APIs, databases, and streaming systems
• Ensure data quality, reliability, and performance tuning of data jobs
• Collaborate with analytics, product, and business teams to support reporting and advanced analytics
• Implement best practices for data governance, security, and monitoring
• Support production deployments and troubleshoot data pipeline issues
Required Skills & Experience
• 7-10 years of experience as a Data Engineer
• Experience in banking or financial services (highly preferred / optional)
• Strong hands-on experience with Databricks
• Expertise in Apache Spark (PySpark / Spark SQL)
• Experience with Delta Lake, data modeling, and performance optimization
• Strong SQL skills and experience with relational & NoSQL databases
• Experience working with cloud platforms (AWS / Azure / GCP)
• Familiarity with orchestration tools like Airflow / Azure Data Factory / similar
• Experience with version control (Git) and CI/CD pipelines
Nice to Have
• Knowledge of streaming technologies (Kafka, Event Hubs, Spark Streaming)
• Experience with data governance, lineage, and security frameworks
