Location
Mumbai | India
Job description
The Hive Architect is responsible for designing and managing data storage and query processing solutions using Apache Hive. This role requires expertise in Hive, Hadoop, and related technologies, along with the ability to design and optimize data structures for efficient data analysis and reporting.
Key Responsibilities - Design and Implementation:
- Design data models and storage structures using Apache Hive to support business requirements.
- Develop and implement HiveQL queries, views, and scripts to process and analyze data.
- Work closely with data engineers and administrators to ensure smooth implementation of data solutions.
- Data Optimization:
- Optimize Hive queries and data processing for performance and efficiency.
- Tune and improve the Hive metastore to enhance query performance.
- Identify and resolve performance bottlenecks and data processing issues.
- Data Integration:
- Integrate Hive with other data sources and tools, such as Hadoop, Spark, and data warehouses.
- Develop ETL (Extract, Transform, Load) processes to move and transform data into Hive tables.
- Security and Access Control:
- Implement security measures to protect data stored in Hive, including authentication and authorization.
- Define and manage access control for Hive tables and data.
- Documentation and Training:
- Document data models, Hive schemas, and query processes for knowledge sharing.
- Provide training and guidance to data analysts and engineers on using Hive effectively.
- Performance Monitoring:
- Monitor the performance of Hive queries and data processing jobs.
- Proactively identify issues and make recommendations for improvements.
- Scalability and High Availability:
- Ensure the scalability and high availability of Hive infrastructure.
- Design and implement failover and disaster recovery solutions.
- Stay Current:
- Stay up-to-date with the latest developments in Hive, Hadoop, and big data technologies.
- Evaluate new tools and technologies that can enhance data processing capabilities.
Qualifications - Bachelor's or higher degree in Computer Science, Information Technology, or a related field.
- Proven experience in designing and implementing data solutions using Apache Hive and Hadoop ecosystem.
- Proficiency in HiveQL, SQL, and scripting languages.
- Strong knowledge of data warehousing concepts, ETL processes, and data integration.
- Experience with performance tuning and optimization of Hive queries.
- Familiarity with security measures and access control in Hive.
- Excellent problem-solving and analytical skills.
- Strong communication and teamwork skills.
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