Remote Data Platform Engineer — Spark & Hadoop Pipelines

Bright Vision Technologies; Franklin, Nashville (TN, TN); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an experienced Data Platform Engineer to design, build, and operate large-scale data pipelines and analytics platforms on Hadoop and related big-data ecosystems. In this role you will ingest, transforming, and analyze massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads.

The ideal candidate will have 6+ years of experience, strong Spark, Hive, HDFS, Kafka, Airflow/Oozie, SQL, and

Qualifications

• 5+ years of professional experience designing and operating big-data pipelines on Hadoop.
• Strong hands‑on expertise with Apache Spark (Scala, Python, or Java) in production environments.
• Solid experience with Hive, HDFS, Sqoop, HBase, and the broader Hadoop ecosystem.
• Hands‑on experience with streaming data platforms such as Kafka, Spark Streaming, or Flink.
• Strong SQL skills and experience working with both relational and NoSQL data stores.
• Experience with workflow orchestration tools such as Airflow or Oozie.
• Solid understanding of distributed systems concepts, including partitioning, replication, and fault tolerance.
• Strong scripting skills in Python or Shell.
• Excellent troubleshooting, debugging, and documentation skills.

Skills

Big-data design & pipelines

Spark (Scala/Python/Java)

SQL & NoSQL

Distributed systems concepts

Troubleshooting & docs

Tools

Apache Hadoop

Hive

HDFS

Sqoop

HBase

Kafka

Spark Streaming

Flink

Airflow

Oozie

Python scripting

Shell scripting

Job description

Bright Vision Technologies is seeking an experienced Data Platform Engineer to design, build, and operate large-scale data pipelines and analytics platforms on Hadoop and related big-data ecosystems. In this role you will ingest, transforming, and analyze massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads.

The ideal candidate will have 6+ years of experience, strong Spark, Hive, HDFS, Kafka, Airflow/Oozie, SQL, and