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AWS data Engineer
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AWS data Engineer

at Upgrad KnowledgeHut

Agency job
3 - 5 yrs
₹8L - ₹15L / yr
Hyderabad
Skills
skill iconAmazon Web Services (AWS)
skill iconData Analytics
Data Visualization
PowerBI
Tableau
Qlikview
Spotfire
Data engineering

AWS Data Engineer:

 

Job Description

  • 3+ years of experience in AWS Data Engineering.

  • Design and build ETL pipelines & Data lakes to automate ingestion of structured and unstructured data

  • Experience working with AWS big data technologies (Redshift, S3, AWS Glue, Kinesis, Athena ,DMS, EMR and Lambda for Serverless ETL)

  • Should have knowledge in SQL and NoSQL programming languages.

  • Have worked on batch and real time pipelines.

  • Excellent programming and debugging skills in Scala or Python & Spark.

  • Good Experience in Data Lake formation, Apache spark, python, hands on experience in deploying the models.

  • Must have experience in Production migration Process

  • Nice to have experience with Power BI visualization tools and connectivity

 

Roles & Responsibilities:

  • Design, build and operationalize large scale enterprise data solutions and applications

  • Analyze, re-architect and re-platform on premise data warehouses to data platforms on AWS cloud.

  • Design and build production data pipelines from ingestion to consumption within AWS big data architecture, using Python, or Scala.

  • Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud.

 

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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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