We are seeking a knowledgeable and enthusiastic Big Data Analytics Instructor to deliver advanced-level training in big data technologies, data engineering, and data analysis techniques. The ideal candidate should have a solid background in handling large datasets, using big data tools, and applying statistical and machine learning techniques for insightful data analysis.

The instructor will be responsible for designing and delivering a hands-on curriculum that prepares students for real-world roles in data science and big data engineering.

Key Responsibilities:

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  Deliver lectures and practical sessions on Big Data tools and technologies

  
  


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  Train students in data collection, storage, processing, analysis, and visualization

  
  


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  Teach frameworks such as Hadoop, Spark, Hive, Pig, Kafka, and NoSQL databases

  
  


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  Introduce data engineering workflows and data pipelines using tools like Apache Airflow, NiFi, etc.

  
  


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  Guide students in handling structured and unstructured data at scale

  
  


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  Cover data analysis and visualization using tools like Python, R, SQL, Power BI, or Tableau

  
  


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  Mentor students through real-world projects, assignments, and case studies

  
  


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  Stay updated with emerging technologies and industry best practices in data analytics and big data

  
  


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  Evaluate student progress and provide constructive feedback

  
  


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  Prepare students for industry roles and certifications

  
  

Requirements:

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  Minimum 16 years of education in Computer Science, Data Science, IT, or a related field

  
  


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  At least 1 year of teaching/training experience

  
  


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  Minimum 3 years of practical experience in big data analytics or data engineering

  
  

Strong command of big data platforms:

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  Hadoop Ecosystem (HDFS, MapReduce, Hive, Pig)

  
  


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  Apache Spark (PySpark, Spark SQL, MLlib)

  
  


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  Kafka, Flume, or Sqoop

  
  


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  NoSQL Databases (MongoDB, Cassandra, HBase)

  
  


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  Proficiency in Python, SQL, and scripting for data manipulation

  
  


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  Knowledge of data visualization tools (Power BI, Tableau, Matplotlib, Seaborn, etc.)

  
  


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  Understanding of ETL pipelines, cloud platforms (AWS, GCP, or Azure), and distributed systems

  
  


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  Excellent communication, presentation, and mentoring skills