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Nitesh Singh
Data Engineer | Python | PySpark | SQL | BigData | AWS/Azure/GCP | Airflow l Informatica
Education
• nsit netaji subhas institute of technology
• iec college of engg and technology
Companies
• tiger analytics
• futurense technologies
• lakshmikumaran and sridharan
Experience
4.3 Years
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Airflow
Amazon Athena
Amazon EC2
Amazon Elastic MapReduce (EMR)
Amazon S3
Amazon Web Services (AWS)
analytics
apache
Apache Airflow
Apache Hive
Apache Spark
AWS Glue
AWS Lambda
Consulting
Data Analysis
Data Analytics
Data Engineering
Data Pipelines
Data Processing
Databricks
Education
Extract, Transform, Load (ETL)
Google Cloud Platform (GCP)
Grafana
Hadoop
HBase
Hive
Informatica
infra
Infrastructure
Kafka
Mechanical Engineering
MongoDB
MySQL
Oracle SQL
Oracle SQL Developer
pyspark
Python
Search
Software Engineer
SQL
Sqoop
storage
Tableau
Contact Details
Email (Verified)
maiXXXXXXXXXXXXXXXXXXXXXXXomMobile Number
+91XXXXXXXX27Education
nsit netaji subhas institute of technology
Master of Technology - MTech
2017 - 2019
iec college of engg and technology
Bachelor of Technology - BTech
2012 - 2016
Frequently asked questions
What company does Nitesh Singh work for?
Nitesh Singh works for tiger analytics
What is Nitesh Singh role in his workplace?
Nitesh Singh's role in his workplace is Data Engineer
What is Nitesh Singh's tenure in his workplace?
Nitesh Singh's tenure in his workplace is 2.75 years
What is Nitesh Singh's total experience?
Nitesh Singh's total experience is 4.33 years
What is Nitesh Singh's LinkedIn profile?
What is Nitesh Singh's email address?
What is Nitesh Singh's phone/WhatsApp number?
What schools did Nitesh Singh attend?
Nitesh Singh has attended nsit netaji subhas institute of technology, iec college of engg and technology
What companies has Nitesh Singh worked with?
Nitesh Singh has worked with tiger analytics, futurense technologies, lakshmikumaran and sridharan
What are some of Nitesh Singh's skills?
Nitesh Singh has skills in Airflow, Amazon Athena, Amazon EC2, Amazon Elastic MapReduce (EMR), Amazon S3, Amazon Web Services (AWS) and more.
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