Data Engineer-Data Platforms-AWS

Role & Responsibilities:

• Develop, maintain, evaluate, and test big data solutions.
• Build data pipelines to ingest, process, and transform data from files, streams, and databases.
• Process data with Spark, Python, PySpark, Scala, and Hive, HBase, or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS.
• Develop efficient software code leveraging Spark Framework / Python or Scala and Big Data technologies for multiple use cases.
• Develop streaming pipelines.
• Work with Hadoop / AWS ecosystem components to implement scalable solutions for increasing data volumes using big data/cloud technologies like Apache Spark, Kafka, or any Cloud computing tools.

Required Education:

• Bachelor's Degree

Preferred Education:

• Master's Degree

Required Technical and Professional Expertise:

• 5-8+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering.
• Minimum 5+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala.
• Minimum 3 years of experience on Cloud Data Platforms on AWS.
• Experience with AWS EMR, AWS Glue, DataBricks, AWS RedShift, DynamoDB.
• Strong SQL skills.

Preferred Technical and Professional Experience:

• Certification in AWS and DataBricks or Cloudera Spark Certified Developer.