Python Developer

Experience- 4-15 Years

Location: Chennai

Job Summary: An experienced PySpark Developer / Leads to design, develop, and maintain large-scale data processing solutions using Apache Spark and Python. The ideal candidate should have a strong background in data engineering, data processing, and cloud-based data platforms, big data ecosystems and performance optimization

Responsibilities:

• Data Processing: Design, develop, and maintain data processing solutions using PySpark, Apache Spark, and Python.
• Data Pipeline Development: Develop and optimize data pipelines using PySpark, Apache Spark, and cloud-based data platforms.
• Data Integration: Integrate data from various sources, including relational databases, NoSQL databases, and cloud storage.
• Data Transformation: Develop and implement data transformation logic using PySpark, Apache Spark, and Python.
• Collaboration: Work with cross-functional teams to identify and prioritize project requirements, provide technical guidance, and ensure data quality.

Required Skills:

• PySpark: In-depth knowledge of PySpark, Apache Spark, and Python.
• Data Processing: Strong understanding of data processing concepts, including data ingestion, data transformation, and data storage.
• Cloud Experience: Experience with cloud-based data platforms, including AWS, Azure, or Google Cloud.
• Expertise in DataFrames & Spark SQL, Spark Streaming with Apache Kafka real-time data ingestion pipelines
• Very good conceptual understanding of Multithreading, distributed computing concepts of Pyspark
• Programming: Proficiency in programming languages, including Python, Java, or Scala.
• Communication: Excellent communication and collaboration skills.

Preferred Skills:

• Apache Spark Certifications: Relevant certifications, such as Apache Spark Certification or Cloudera Certified Spark Developer.
• Big Data: Experience with big data technologies, including Hadoop, HBase, or Cassandra.
• Machine Learning: Experience with machine learning frameworks, including TensorFlow, PyTorch, or Scikit-learn.
• Data Science: Experience with data science tools, including Jupyter Notebook, Pandas, or NumPy