Hadoop Big Data Developer

Bright Vision Technologies•Schaumburg, IL
•$86,000 - $103,000•Remote

About The Position

Bright Vision Technologies is seeking an experienced Hadoop Big Data Developer to design, build, and operate large-scale data processing pipelines and analytics platforms using Hadoop and related big-data ecosystems. The role involves ingesting, transforming, and analyzing large volumes of structured and unstructured data for enterprise analytics, machine learning, and reporting workloads. The successful candidate will bring deep Hadoop ecosystem expertise and strong software engineering fundamentals to deliver reliable, performant, and cost-effective production data platforms. This is a full-time, direct W2 position that is 100% remote within the United States. The annual salary range is $86,000–$103,000. U.S. citizens, Green Card holders, EAD holders, and candidates eligible for an H-1B transfer are encouraged to apply; the employer cannot sponsor new H-1B visa petitions for this position.

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 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.

Nice To Haves

  • Experience operating Hadoop on cloud platforms such as AWS EMR, Azure HDInsight, or Databricks.
  • Familiarity with modern lakehouse formats such as Delta, Iceberg, and Hudi.
  • Exposure to data governance tooling such as Apache Atlas or Collibra.
  • Experience with Kubernetes-based data platforms, including Spark-on-K8s and Trino.
  • Hands-on experience with CI/CD and infrastructure-as-code in data engineering workflows.

Responsibilities

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