Big Data Engineer

Role Overview

Join an established and well-respected organization offering tremendous career growth potential as a Big Data Engineer. Design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related big-data ecosystems. Ingest, transform, and analyze massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads.

What You Will Do

Responsible for designing and operating big-data pipelines on Hadoop, ingesting, transforming, and analyzing massive volumes of structured and unstructured data, and delivering reliable, performant, and cost-effective data platforms in production environments.

Why It Might Be a Fit

The ideal candidate will combine deep technical expertise across the Hadoop ecosystem with strong software engineering fundamentals and a clear understanding of how to deliver reliable, performant, and cost-effective data platforms in production environments.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
• Five or more 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.

Benefits

• Salary Range: $100,000–$150,000 Annually