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6-8 Years
Early Applicant
  • Posted 22 hours ago
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Job Description

Experience-6 to 8 Years

Location: Chennai

Job Summary: An experienced Python Developer 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 Kafkareal-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

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