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Senior Python and PySpark Data Engineer

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Bengaluru, Karnataka, India beBeeDataEngineer Full time
Senior Python and PySpark Data Engineer

We are seeking an experienced Senior Python and PySpark Data Engineer to join our team. As a key member of our data engineering team, you will be responsible for designing, developing, and maintaining complex data processing systems using Python and PySpark.

Your primary focus will be on developing efficient and scalable data pipelines that can handle diverse data sources and formats. You will work closely with cross-functional teams, including data scientists, product managers, and operations engineers, to understand business needs and translate them into technical solutions.

To succeed in this role, you should have a strong background in Python programming and experience with PySpark. A deep understanding of object-oriented programming concepts and functional programming paradigms is essential. Additionally, you should be proficient in GitOps principles and have experience with infrastructure as code.

Responsibilities:
  • Design, develop, and maintain robust data processing pipelines using Python and PySpark.
  • Implement data ingestion strategies to ensure timely and accurate data entry into your systems.
  • Apply GitOps principles to manage infrastructure as code, ensuring consistent and reliable deployment of applications across various environments.
  • Work closely with cross-functional teams to understand business needs and translate them into technical solutions.
  • Stay updated with the latest trends and technologies in data processing and contribute to the continuous improvement of existing systems.
Requirements:
  • Bachelor's degree in computer science, Data Science, or a related field.
  • Certifications in Python, PySpark, or Big Data technologies (e.g., Cloudera Certified Data Engineer, AWS Certified Data Analytics Specialty).
  • Minimum 5 years of professional experience in developing data processing solutions using Python and PySpark.
Preferred Qualifications:
  • Strong expertise in handling large datasets using Hadoop, Spark, and other big data technologies.
  • Experience with data visualization tools and techniques.
  • Knowledge of cloud-based services and platforms (e.g., AWS, Azure, GCP).