Design and architect scalable data platforms with Databricks and Spark. Lead data lake implementations, define governance practices, and optimize performance.
- Design and architect scalable data platforms using Databricks and Apache Spark.
- Lead end-to-end implementation of data lakes, lakehouse, and analytics solutions.
- Define data engineering, security, and governance best practices.
- Collaborate with data engineers, data scientists, and business stakeholders.
- Optimize performance, cost, and reliability of Databricks workloads.
Requirements
- Strong hands-on experience with Databricks, Spark, and Delta Lake.
- Proficiency in Python/Scala and SQL for big data processing.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Solid understanding of data architecture, ETL/ELT, and data modeling.
- Excellent communication and solution-design skills.
Requirements
- Strong hands-on experience with Databricks, Spark, and Delta Lake.
- Proficiency in Python/Scala and SQL for big data processing.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Solid understanding of data architecture, ETL/ELT, and data modeling.
- Excellent communication and solution-design skills.
Top Skills
Spark
AWS
Azure
Databricks
Delta Lake
GCP
Python
Scala
SQL
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