Remote Big Data Engineer — Spark, Hadoop & Pipelines

Bright Vision Technologies

Orlando (FL)

Remote

USD 100,000 - 150,000

Full time

4 days ago

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Job summary

Bright Vision Technologies is seeking an experienced Big Data Application Developer to design, build, and operate large-scale data processing pipelines on Hadoop and related ecosystems.

In this role you will ingest, transform, and analyze massive data to support analytics, ML, and reporting workloads, delivering reliable data platforms in production.

This 100% remote role is for United States residents with 6+ years of experience and strong expertise in Spark, Hive, SQL, and streaming.

Qualifications

Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
5+ years of experience designing and operating big-data pipelines on Hadoop.
Hands-on expertise with Apache Spark in production environments.
Solid experience with Hive, HDFS, Sqoop, HBase, and Hadoop ecosystem.
Experience with streaming platforms such as Kafka, Spark Streaming, or Flink.
Strong SQL skills with relational and NoSQL data stores.
Experience with workflow orchestration tools such as Airflow or Oozie.
Scripting in Python or Shell.
Understanding of distributed systems concepts including partitioning, replication, and fault tolerance.

Skills

Distributed systems concepts

Troubleshooting

Documentation

SQL

Python scripting

Shell scripting

Education

Bachelor's degree in Computer Science, Engineering, or related

Tools

Apache Spark

Hive

HDFS

Sqoop

HBase

Kafka

Airflow

Oozie

Python

Shell

Job description

Bright Vision Technologies is seeking an experienced Big Data Application Developer to design, build, and operate large-scale data processing pipelines on Hadoop and related ecosystems.

In this role you will ingest, transform, and analyze massive data to support analytics, ML, and reporting workloads, delivering reliable data platforms in production.

This 100% remote role is for United States residents with 6+ years of experience and strong expertise in Spark, Hive, SQL, and streaming.

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