Big Data Developer

L3 Big data

developer:

1. Design, develop, and implement highly scalable and distributed big data

solutions using Hadoop ecosystem technologies such as HBase, Hive, Kudu, and

Spark.

2. Architect HBase schemas and data models to accommodate evolving business

requirements and ensure optimal performance for data storage and retrieval

operations.

3. Develop complex Hive queries and data processing pipelines to transform raw

data into structured formats suitable for analysis and reporting.

4. Implement data ingestion pipelines using Spark Streaming and Spark SQL for

real-time processing of streaming data sources, ensuring high throughput and

low latency.

5. Optimize Spark applications for performance and resource utilization,

including tuning RDD transformations, optimizing data partitioning strategies,

and leveraging in-memory caching.

6. Utilize advanced features of Spark MLlib for machine learning tasks such as

classification, regression, clustering, and collaborative filtering.

7. Design and deploy Kudu tables for fast analytical queries and real-time

analytics, leveraging Kudus unique combination of fast analytics and fast data

ingestion.

8. Collaborate with data scientists to integrate machine learning models into

Spark workflows and productionize them for real-time predictions and analytics.

9. Troubleshoot performance bottlenecks, data quality issues, and system

failures in big data applications and infrastructure, and implement solutions

to address them.

10. Stay abreast of emerging technologies and best practices in big data processing

and analytics, and evaluate their potential impact on our architecture and

solutions.