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Zensar

Data Engineer (AWS+Pyspark)

Zensar Hyderabad, Telangana, India

IT Services and IT Consulting · 10,001+ employees

6 d ago
data-engineer Senior (5-10 yrs) Full-time India
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About the role

Build and optimize PySpark applications to process large volumes of data using AWS analytics services. Manage data pipelines and ensure efficient data storage using columnar formats and compression techniques.

What they look for

Python Pyspark AWS Big Data Amazon EMR Amazon Athena AWS Glue Git Amazon Lambda Amazon EC2 S3 Data Warehousing Parquet Snappy Gzip SQL

Requirements

Requires 6-10 years of experience in Big Data technologies with mandatory proficiency in Python and PySpark. Candidates should have hands-on experience with AWS services like EMR, Athena, Glue, and version control tools like Git.

Full description

Data Engineer (AWS + pySpark)

  • Having 6+ yrs years of relevant experience, which includes hands on experience in Big Data technologies.
  • Mandatory - Hands on experience in Python and PySpark.
  • Build pySpark applications using Spark Dataframes in Python.
  • Worked on optimizing spark jobs that processes huge volumes of data.
  • Hands on experience in version control tools like Git.
  • Worked on Amazon’s Analytics services like Amazon EMR, Amazon Athena, AWS Glue.
  • Worked on Amazon’s Compute services like Amazon Lambda, Amazon EC2 and Amazon’s Storage service like S3 and few other services like SNS.
  • Good to have knowledge of datawarehousing concepts – dimensions, facts, schemas- snowflake, star etc.
  • Have worked with columnar storage formats - Parquet etc. Well versed with compression techniques – Snappy, Gzip.
  • Good to have knowledge of AWS databases (atleast one) Aurora, RDS, Redshift, ElastiCache, DynamoDB.am

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