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Senior Data Engineer (Python, PySpark, Kafka) at Bosch Group

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

23 Aug, 26

Salary

0.0

Posted On

25 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PySpark, Apache Kafka, Hadoop, HDFS, YARN, Hive, SQL, PostgreSQL, SQL Server, Data Warehousing, Dimensional Modeling, Git, GitHub

Industry

Software Development

Description

Company Description Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region. Job Description **Key Responsibilities:** Develop and maintain robust Python code for data manipulation, scripting, and application development Design and build high-performance data transformation jobs using PySpark on large-scale datasets Build and maintain real-time data streaming pipelines using Apache Kafka, including Kafka Connect and Kafka Streams implementations Work with the Hadoop ecosystem, including HDFS, YARN, Hive, and related technologies Extract, query, and manage data using SQL and relational databases (e.g., PostgreSQL, SQL Server) Apply data warehousing concepts and dimensional modeling principles to optimize data architecture Manage code repositories and collaborate with teams using version control systems (e.g., Git, GitHub) Qualifications B.Tech, M.Tech Additional Information 6 to 9 Years Legal Entity: Bosch Global Software Technologies Private Limited

Responsibilities

Develop and maintain robust Python code and high-performance data transformation jobs using PySpark. Build real-time data streaming pipelines with Apache Kafka and manage data within the Hadoop ecosystem.