Big Data Engineer

2 months ago

Bengaluru, India ADVANSOFT Full time

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.

- 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 end-to-end 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.

Experiences :

- Nice to have development experience in Python-based 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 multi-task across multiple projects, interface with external and internal resources, and provide technical leadership to junior team members.

- Ability to be high-energy, detail-oriented, proactive, and able to function under pressure in an independent environment along with a high degree of initiative and self-motivation 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.

(ref:hirist.tech)

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