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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We work with product organizations to help them scale or modernize their legacy technology solutions. We work with startups to help them operationalize their idea efficiently. We work with large established institutions to help them create internal applications to automate manual opperations and achieve scale.
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