Senior Python Engineer for Data Retraining
Are you prepared to take your Python engineering expertise to the next level and transition into the dynamic world of Big Data? EPAM provides a unique chance to secure a role after passing a single technical interview, while acquiring Big Data skills without changing your title or compensation.
This focused 8-week program is tailored for Python engineers making the shift to Big Data Engineering. The curriculum encompasses three distinct phases: theoretical coursework delivered by industry professionals, practical tasks or hands-on projects, and a well-rounded knowledge assessment accompanied by feedback. Key topics include data management, distributed systems, Spark, Kafka, NoSQL databases, and cloud-native services, ensuring a solid grounding in modern data platforms. The training is fully remote, enabling participants to learn from the comfort of their own space.
Responsibilities
- Develop a strong foundation in Big Data by exploring core concepts, Hadoop infrastructure, real-world applications, data characteristics, and deployment trends
- Build familiarity with DevOps practices, including continuous integration and continuous deployment (CI/CD), to enhance software development and operational workflows
- Acquire essential data modeling techniques critical for managing and interpreting complex data structures in engineering and architectural roles
- Expand knowledge of Apache Spark by understanding its architecture, components, and functionalities such as Spark SQL, Spark ML, and Spark Streaming
- Gain expertise in Kafka fundamentals and tools like Kafka Connect and Kafka Streams for managing real-time data feeds and performing stream processing
- Explore Elastic Stack for real-time data analysis and visualization while understanding NoSQL databases to manage diverse data types
- Deepen understanding of data flow and pipelining with tools like NiFi and Streamsets to improve data collection, flow, and processing capabilities
- Learn orchestration and workflow management with tools such as Airflow and Jenkins to coordinate complex processes effectively
Requirements
- 4+ years of production experience in IT
- Proficiency in Python, SQL, and cloud platforms (AWS, GCP, Azure)
- Background in tools such as Databricks, Spark, Docker, Kubernetes is a plus
- Familiarity with AI, LLM
- English proficiency at B2+ or higher
