dataeaze systems
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Amazon Web Services (AWS)
PythonPOST - SENIOR DATA ENGINEER WITH AWS
Experience : 5 years
Must-have:
• Highly skilled in Python and PySpark
• Have expertise in writing Glue jobs ETL script, AWS
• Experience in working with Kafka
• Extensive SQL DB experience – Postgres
Good-to-have:
• Experience in working with data analytics and modelling
• Hands on Experience of PowerBI visualization tool
• Knowledge and hands-on on version control system - Git Common:
• Excellent communication and presentation skills (written and verbal) to all levels
of an organization
• Should be results oriented with ability to prioritize and drive multiple initiatives to
complete work you're doing on time
• Proven ability to influence a diverse geographically dispersed group of
individuals to facilitate, moderate, and influence productive design and implementation
discussions driving towards results
Shifts - Flexible ( might have to work as per US Shift timings for meetings ).
Employment Type - Any
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Java- Core Java: advanced level competency, should have worked on projects with core Java development.
- Linux shell : advanced level competency, work experience with Linux shell scripting, knowledge and experience to use important shell commands
- Rdbms, SQL: advanced level competency, Should have expertise in SQL query language syntax, should be well versed with aggregations, joins of SQL query language.
- Data structures and problem solving: should have ability to use appropriate data structure.
- AWS cloud : Good to have experience with aws serverless toolset along with aws infra
- Data Engineering ecosystem : Good to have experience and knowledge of data engineering, ETL, data warehouse (any toolset)
- Hadoop, HDFS, YARN : Should have introduction to internal working of these toolsets
- HIVE, MapReduce, Spark: Good to have experience developing transformations using hive queries, MapReduce job implementation and Spark Job Implementation. Spark implementation in Scala will be plus point.
- Airflow, Oozie, Sqoop, Zookeeper, Kafka: Good to have knowledge about purpose and working of these technology toolsets. Working experience will be a plus point here.
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