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