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Data Engineer

  • Job type Posted on: Jul 24, 2026
  • Experience level American IT Systems
  • Employment type Alpharetta, Georgia
  • Employment type Onsite
  • Salary CTC

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Job Title :

Data Engineer

Job Type :

CTC

Job Location :

Alpharetta Georgia United States

Remote :

No

Jobcon Logo Job Description :

Data Engineer

Alpharetta GA or Berkley Heights NJ

5days onsite

Rate :: 65-67/hr. on C2C

Primary skills:

Data Engineering; Databricks; Hadoop; Splunk, Talend, Spark Job

Description Years of Experience

4 to 8 years' experience Comprehensive understanding of Hadoop, HDFS, and cloud Big Data technologies, with hands-on experience in managing and processing vast amounts of data effectively.

Advanced knowledge of Apache Spark to handle large-scale data processing tasks, including the development and optimization of complex Spark applications for efficient data transformation.

Hands-on experience in building and optimizing data processing applications using Java and Python, ensuring high performance and scalability of data pipelines.

Note from Client - On the Cloud technologies, lets make sure they have worked on Databricks.

Jobcon Logo Position Details

Posted:

Jul 24, 2026

Reference Number:

1393-44639

Employment:

CTC

Salary:

Not Available

City:

Alpharetta

Job Origin:

CIEPAL_ORGANIC_FEED

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Data Engineer

Alpharetta GA or Berkley Heights NJ

5days onsite

Rate :: 65-67/hr. on C2C

Primary skills:

Data Engineering; Databricks; Hadoop; Splunk, Talend, Spark Job

Description Years of Experience

4 to 8 years' experience Comprehensive understanding of Hadoop, HDFS, and cloud Big Data technologies, with hands-on experience in managing and processing vast amounts of data effectively.

Advanced knowledge of Apache Spark to handle large-scale data processing tasks, including the development and optimization of complex Spark applications for efficient data transformation.

Hands-on experience in building and optimizing data processing applications using Java and Python, ensuring high performance and scalability of data pipelines.

Note from Client - On the Cloud technologies, lets make sure they have worked on Databricks.

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