Manager Data Modeler
2 months ago
Data Pipeline Development:
Design & guiding developers in develop and maintain data processing pipelines using PySpark.
Collaborate with data engineers and analysts to integrate data from various sources.
Implement data transformations, aggregations, and enrichment processes.
Performance Optimization: **
Guiding in optimize Spark jobs for performance and scalability.
Monitor and troubleshoot performance issues in Spark applications.
Implement best practices for efficient Spark code and resource utilization.
Data Model Design & Development
Understanding of Life Insurance Industry leading to design & establish data models in GCP cloud and adhering to enterprise standards.
Evaluate data related tools and technologies and recommend appropriate implementation patterns and standards methodologies to ensure latest and modern data architecture & data rules implementation.
Create and maintain conceptual / logical data models to identify key business entities and visual relationship resulting in efficient data pipelines and optimized and non-redundant data.
Reviewing data models with both technical and business audiences
Experience
5 years of experience with cloud platforms (Google Cloud) and their data services are desirable.
Proficiency in Python and PySpark.
Experience with Hadoop ecosystem (HDFS, Hive, HBase) is a plus.
Technical Skills
Strong understanding of distributed computing principles.
Experience with data modeling, ETL processes, and data warehousing Google BigQuery
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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