AWS Data Engineer chez Cognizant

%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3ESkills- AWS Data Engineer%3Co:p%3E%3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3EExperience: 9 to 13 years%3Co:p%3E%3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3ELocation: AIA-Pune%3Co:p%3E%3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3E%3Co:p%3E %3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3EWe are seeking skilled and dynamic Cloud Data Engineers specializing in AWS, Databricks. The ideal candidate will have a strong background in data engineering, with a focus on data ingestion, transformation, and warehousing. They should also possess excellent knowledge of PySpark or Spark, and a proven ability to optimize performance in Spark job executions.%3Co:p%3E%3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3EKey Responsibilities:%3Co:p%3E%3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3E- %3C/strong%3EDesign, build, and maintain scalable data pipelines for a variety of cloud platforms including AWS.%3Co:p%3E%3C/o:p%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E- Implement data ingestion and transformation processes to facilitate efficient data warehousing. - Utilize cloud services to enhance data processing capabilities:%3Co:p%3E%3C/o:p%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E- AWS: Glue, Athena, Lambda, Redshift, Step Functions, DynamoDB, SNS.%3Co:p%3E%3C/o:p%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E- Optimize Spark job performance to ensure high efficiency and reliability. - Stay proactive in learning and implementing new technologies to improve data processing frameworks. - Collaborate with cross-functional teams to deliver robust data solutions. - Work on Spark Streaming for real-time data processing as necessary.%3Co:p%3E%3C/o:p%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Co:p%3E %3C/o:p%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3EQualifications:%3Co:p%3E%3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E-%26nbsp;5-8 years%26nbsp;of experience in data engineering with a strong focus on cloud environments. - Proficiency in PySpark or Spark is mandatory. - Proven experience with data ingestion, transformation, and data warehousing. - In-depth knowledge and hands-on experience with cloud services(AWS): - Demonstrated ability in performance optimization of Spark jobs. - Strong problem-solving skills and the ability to work independently as well as in a team. - Cloud Certification (AWS) is a plus. - Familiarity with Spark Streaming is a bonus.%3Co:p%3E%3C/o:p%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp class=%22MsoNormal%22 style=%22margin-bottom:0cm;%22%3E%3Cspan style=%22font-family:%26quot;Calibri%26quot;,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:115%;%22%3E%3Cstrong%3E%3Co:p%3E %3C/o:p%3E%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E Postuler maintenant