Senior Python Software Engineer for Big Data Retraining program

EPAM·Ukraine·Удалённо·5 мес. назад

Are you ready to elevate your Python engineering skills and transition into the exciting field of Big Data? EPAM is offering a unique opportunity where you can secure a position after a single technical interview and gain Big Data expertise without affecting your title or compensation.

This 8-week retraining program is designed to transition Python engineers into the role of Big Data engineer. The curriculum is divided into three key phases: theoretical coursework led by production specialists, hands-on projects or practical tasks, and comprehensive knowledge assessment with feedback. Covering essential topics such as data management, distributed systems, Spark, Kafka, NoSQL databases, and cloud-native services, the program offers a robust foundation in data processing platforms. Training is fully online, allowing participants to engage remotely.

Responsibilities

Explore Big Data and Hadoop: Gain a solid understanding of Big Data concepts, delve into Hadoop’s infrastructure and real-world applications, and learn about data characteristics and deployment trends
Understand DevOps Practices: Familiarize yourself with the basics of DevOps, including continuous integration and continuous deployment (CI/CD), and how these practices streamline software development and operations
Master Data Modeling and Architectures: Learn the essential techniques and levels of data modeling, crucial for Data Engineers and Architects, to effectively manage and interpret complex data structures
Dive into Apache Spark: Deepen your knowledge of Spark with detailed explorations of its architecture, components, and various functionalities including Spark SQL, Spark ML, and Spark Streaming
Harness the Power of Kafka: Understand the fundamentals of Kafka, and explore Kafka Connect and Kafka Streams to manage real-time data feeds and perform stream processing
Leverage Elastic Stack and NoSQL: Get hands-on experience with Elastic Stack for searching, analyzing, and visualizing data in real time, and explore NoSQL databases to manage large volumes of structured, semi-structured, and unstructured data
Implement Data Flow and Pipelining: Learn about data movement essentials and tools like NiFi and Streamsets for effective data collection, flow, and processing
Navigate Orchestration and Scheduling: Understand the role of orchestration in managing complex workflows using tools like Airflow and Jenkins