Data Engineer


CLPS Global
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Job Details
Skills
- Apache HBase
- Python
- PySpark
- Data Analysis
- Apache Spark
- Apache Hive
- Engineering Design
- Database
Summary
- Design, develop, and maintain software solutions using Python.
- Developed Python and pyspark programs for data analysis.. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine).
- Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD''''s were used to apply business transformations and utilized Hive Context objects to perform read/write operations..
- Develop back-end services, APIs, and integrate databases.
- Optimize applications for performance, security, and maintainability.
- Troubleshoot and resolve software defects and issues.
Required Skills:
- Strong proficiency in Python and Spark.
- Dice Id: 91131444
- Position Id: 8913663
- Posted 2 days ago
Company Info
CLPS is a NASDAQ-listed (Nasdaq: CLPS) and global information technology, consulting and solutions service provider focused on delivering services to global institutions in banking, insurance and the financial sectors, both in China and globally.
For more than ten years as an IT, business know-how and talent solutions provider for such clients, CLPS has expanded its service network to clients in the global financial industry, including large financial institutions from the US, Europe, Australia and Hong Kong and their PRC-based IT centers.
CLPS has created and developed a particular market niche by providing turn-key financial solutions as well as supplying its clients’ needs for talent creation and development.
We maintain 18 delivery and R&D centers, of which ten are located in China and eight globally, to serve different customers in various geographic locations. By combining onsite and onshore support and consulting with scalable and high-efficiency offsite and offshore services and processing, we are able to meet client demands in a cost-effective manner while retaining significant operational flexibility.

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