- Experience working with Databases like Oracle, and Netezza and have strong SQL knowledge.
- Developing scalable streaming solutions based on Hadoop/ Big Data stack such as HDFS, Ozone, Hive/ Impala, Apache Spark, and Kafka.
- Experience in Data Engineering and implementation. multiple e endtoend DW projects in a Big Data environment.
- Experience in building data pipelines through Git, Shell, Spark with Java/ Python on Hadoop, or Object storage (S3/CEPH).
- Strong analytical skills are required for debugging production issues, providing root causes, and implementing mitigation plans.
- Strong communication skills, both verbal and written and strong relationship, collaboration skills, and organizational skills.
- Flexible enough to stretch and work in India time to coordinate with the India team.
- Nice to have development experience in Pythonbased Al/ML workloads on Hadoop.
- Experience working on Nifi, APLS, and Unix Environments will be an added advantage.
- Experience of working in Agile teams.
- Ability to multitask across multiple projects, interface with external and internal resources, and provide technical leadership to junior team members.
- Ability to be highenergy, detailoriented, proactive, and able to function under pressure in an independent environment along with a high degree of initiative and selfmotivation to drive results.
- Ability to quickly learn and implement new technologies and perform POC to explore the best solution for the problem statement.
- Contribute ideas to help ensure that required standards and processes are in place and actively look for opportunities to enhance standards and improve process efficiency.
- Perform assigned tasks and production incidents independently.
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Big Data Engineer - Bangalore/Chennai/Pune, India - ADVANSOFT
Description
We are hiring for Data engineer with top most MNC client;Exp : 5+years
Np :
immediate to 15days
Location :
& Responsibilities :
5+ years of working experience in ETL scalable data pipeline usin61Scala, Python, Pyspark, Hadoop, Apache Spark, Spark SQL, Kafka, Nill, and incremental Data Load with Big data technologies.
Experiences :