Welcome to Celcom Solutions. Be a part of our global team! We are looking for people who would love to ideate, educate and foster in the workplace and have a strong will to showcase their capabilities and help our business to grow. At Celcom, each employee matters, and we strongly empower individuals willing to make a difference. Come and join us and be a part of this diverse team!
Benefits at Celcom
Learn from the experts in the Telecom Domain
You grow as the Company grows
Flexible Work Hours
Work from Home Flexibility
Competitive salary package and benefits
You own your work
Equal Employment Opportunities
Rewards and Recognition
Health Insurance
Leave Benefits
Bonus
Notice Period
Immediate joiners only.
- Should be able to design, develop, and implement highly scalable and distributed big data solutions using Hadoop ecosystem technologies such as HBase, Hive, Kudu, and Spark.
- Should have knowledge on Architect HBase schemas and data models to accommodate evolving business requirements and ensure optimal performance for data storage and retrieval operations.
- Should have knowledge on developing complex Hive queries and data processing pipelines to transform raw data into structured formats suitable for analysis and reporting.
- Implement data ingestion pipelines using Spark Streaming and Spark SQL for real-time processing of streaming data sources, ensuring high throughput and low latency.
- Optimize Spark applications for performance and resource utilization, including tuning RDD transformations, optimizing data partitioning strategies, and leveraging in-memory caching.
- Utilize advanced features of Spark MLlib for machine learning tasks such as classification, regression, clustering, and collaborative filtering.
- Design and deploy Kudu tables for fast analytical queries and real-time analytics, leveraging Kudu’s unique combination of fast analytics and fast data ingestion.
- Collaborate with data scientists to integrate machine learning models into Spark workflows and productionize them for real-time predictions and analytics.
- Troubleshoot performance bottlenecks, data quality issues, and system failures in big data applications and infrastructure, and implement solutions to address them.
- Stay abreast of emerging technologies and best practices in big data processing and analytics, and evaluate their potential impact on our architecture and solutions.
