Senior Hadoop & Big Data Engineer — Remote

Bright Vision Technologies; Shrewsbury (MA); On-site; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an experienced Hadoop Big Data Developer to design, build, and operate large-scale data processing pipelines on Hadoop and related ecosystems. You will ingest, transform, and analyze massive data to support analytics, machine learning, and reporting workloads, delivering reliable, performant platforms.

The ideal candidate has 10+ years of experience, hands-on Spark and Hadoop expertise, and a track record of delivering scalable data solutions in production

Qualifications

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

Responsibilities

• Design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related ecosystems.
• Ingest, transform, and analyze massive volumes of structured and unstructured data to support analytics, ML, and reporting workloads.
• Deliver reliable, performant, and cost-effective data platforms in production environments.

Skills

Apache Spark

SQL

Python

Shell scripting

Distributed systems

Kafka

Hive

HDFS

Airflow

Spark Streaming

Education

Bachelor’s degree in CS/Engineering

Tools

Sqoop

Kubernetes

CI/CD

Job description

Bright Vision Technologies is seeking an experienced Hadoop Big Data Developer to design, build, and operate large-scale data processing pipelines on Hadoop and related ecosystems. You will ingest, transform, and analyze massive data to support analytics, machine learning, and reporting workloads, delivering reliable, performant platforms.

The ideal candidate has 10+ years of experience, hands-on Spark and Hadoop expertise, and a track record of delivering scalable data solutions in production