AWS + Pyspark

Job Description: As an AWS Data Engineer (PySpark) at TCS, you will be responsible for utilizing your 5 to 10 years of experience to work with AWS Redshift, Glue, and PySpark. You will have a strong hands-on experience in Python programming and PySpark, along with using AWS services such as RedShift, Glue, EMR, S3, and Lambda. Your role will involve working with Apache Spark and the Hadoop ecosystem, writing and optimizing SQL for data manipulations, and having good exposure to scheduling tools, with Airflow being preferable. You must also have experience in data warehouse technologies like AWS Redshift or Hive, and implementing security measures for data protection. Key Responsibilities: - Utilize AWS Redshift, Glue, and PySpark for data engineering tasks - Work with Python programming and optimize SQL for data manipulations - Utilize AWS services such as RedShift, Glue, EMR, S3, and Lambda - Collaborate with Apache Spark and the Hadoop ecosystem - Implement security measures for data protection - Have exposure to scheduling tools, with Airflow being preferable Qualifications Required: - Bachelor of Engineering - 5 to 10 years of experience in AWS Data Engineering - Strong hands-on experience in Python programming and PySpark - Experience with AWS services like RedShift, Glue, EMR, S3, and Lambda - Experience working with Apache Spark and the Hadoop ecosystem - Experience in writing and optimizing SQL for data manipulations - Exposure to scheduling tools, with Airflow being preferable - Data warehouse experience with AWS Redshift or Hive Please note: Additional details about the company are not included in the provided job description. Job Description: As an AWS Data Engineer (PySpark) at TCS, you will be responsible for utilizing your 5 to 10 years of experience to work with AWS Redshift, Glue, and PySpark. You will have a strong hands-on experience in Python programming and PySpark, along with using AWS services such as RedShift, Glue, EMR, S3, and Lambda. Your role will involve working with Apache Spark and the Hadoop ecosystem, writing and optimizing SQL for data manipulations, and having good exposure to scheduling tools, with Airflow being preferable. You must also have experience in data warehouse technologies like AWS Redshift or Hive, and implementing security measures for data protection. Key Responsibilities: - Utilize AWS Redshift, Glue, and PySpark for data engineering tasks - Work with Python programming and optimize SQL for data manipulations - Utilize AWS services such as RedShift, Glue, EMR, S3, and Lambda - Collaborate with Apache Spark and the Hadoop ecosystem - Implement security measures for data protection - Have exposure to scheduling tools, with Airflow being preferable Qualifications Required: - Bachelor of Engineering - 5 to 10 years of experience in AWS Data Engineering - Strong hands-on experience in Python programming and PySpark - Experience with AWS services like RedShift, Glue, EMR, S3, and Lambda - Experience working with Apache Spark and the Hadoop ecosystem - Experience in writing and optimizing SQL for data manipulations - Exposure to scheduling tools, with Airflow being preferable - Data warehouse experience with AWS Redshift or Hive Please note: Additional details about the company are not included in the provided job description.