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aws sql python databricks apache spark📋 Description
- Design, implement, and optimize big data pipelines in Databricks.
- Develop scalable ETL workflows to process large datasets.
- Leverage Apache Spark for distributed data processing and real-time analytics.
- Implement data governance, security policies, and compliance standards.
- Optimize data lakehouse architectures for performance and cost-efficiency.
- Collaborate with data scientists, analysts, and engineers to enable AI/ML workflows.
🎯 Requirements
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
- 5+ years of hands-on experience with Databricks and Apache Spark.
- Proficiency in SQL, Python, or Scala for data processing and analysis.
- Experience with cloud platforms (AWS, Azure, or GCP) for data engineering.
- Strong knowledge of ETL frameworks, data lakes, and Delta Lake architecture.
- Experience with CI/CD tools and DevOps best practices.
🎁 Benefits
- Hybrid flexibility: 3 days/wk in downtown Toronto; Calgary applicants welcome.
- Fully covered health, dental, and vision insurance from day one.
- Growth & Learning: continuous opportunities and technical direction.
- Inclusive culture and accommodation support.
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