Data Modeler Lead
1 month ago
Data Pipeline Development:
Create and maintain scalable data processing pipelines using PySpark, collaborating with data engineers and analysts to integrate data from various sources.
Performance Optimization:
Develop and implement best practices for efficient Spark code and resource utilization, guiding developers in optimizing Spark jobs for performance and scalability.
Data Model Design & Development:
Design and establish data models in GCP cloud, adhering to enterprise standards, and evaluate data-related tools and technologies to recommend appropriate implementation patterns and standards methodologies.
Key Responsibilities:
- Develop and maintain data models in GCP cloud.
- Collaborate with data engineers and analysts to integrate data from various sources.
- Implement data transformations, aggregations, and enrichment processes.
- Optimize Spark jobs for performance and scalability.
- Evaluate data-related tools and technologies.
Requirements:
- 5 years of experience with cloud platforms (Google Cloud) and their data services.
- Proficiency in Python and PySpark.
- Experience with Hadoop ecosystem (HDFS, Hive, HBase) is a plus.
- Strong understanding of distributed computing principles.
- Knowledge of SQL and NoSQL databases.
- Familiarity with version control systems (e.g., Git).
Soft Skills:
- Excellent problem-solving and analytical skills.
- Strong communication and interpersonal skills.
- Ability to work effectively in a team-oriented environment.
- Self-motivated with a proactive attitude towards learning and development.
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