Hadoop Developer Jobs in USA 2026 with Visa Sponsorship

May 24, 2026 5:03 pm

Hadoop Developer Jobs in USA 2026 with Visa Sponsorship

This Hadoop Developer opportunity is designed for experienced data engineering professionals seeking remote work in the United States. The role focuses on building scalable big data systems that support enterprise analytics, machine learning, and reporting solutions. Additionally, candidates will design and maintain large scale data pipelines using Hadoop ecosystem technologies and modern distributed systems tools. The position involves working with massive structured and unstructured datasets to enable efficient business decision making.

Furthermore, this role requires strong engineering expertise in data pipeline development and performance optimization. Developers will work with technologies such as Spark, Hive, Kafka, HBase, and distributed storage systems. In addition, the role includes responsibilities around data transformation, ingestion, and workflow orchestration in production environments. Overall, this opportunity suits experienced engineers passionate about big data systems and scalable data infrastructure development.

About the Hiring Firm

Bright Vision Technologies is a forward thinking software development company focused on building innovative digital and data driven solutions. The organization specializes in helping businesses automate processes, optimize operations, and improve decision making through technology. Additionally, the company operates with a strong emphasis on scalable architecture, secure systems, and user friendly applications. Its engineering culture encourages innovation, technical excellence, and continuous learning across all teams.

Furthermore, Bright Vision Technologies operates fully remote engagements within structured long term delivery programs. The company emphasizes direct hiring practices and maintains a strong focus on engineering quality and accountability. In addition, it supports career growth through exposure to modern data engineering tools and enterprise scale projects. Ultimately, the organization aims to deliver high performance solutions that transform business operations through advanced technology.

Job Duties

Design and build end to end big data pipelines using Hadoop ecosystem tools and distributed computing frameworks.
Ingest data from relational, file based, streaming, and API sources into scalable data processing systems.
Develop ETL and ELT workflows using Spark Hive Pig and Sqoop with strong focus on data quality.
Build and maintain streaming pipelines using Kafka Spark Streaming or Flink for real time data processing.
Optimize Spark and MapReduce jobs through partitioning memory tuning and performance improvement techniques.
Design data models and storage structures using HDFS Hive HBase and modern lakehouse formats.
Implement data governance lineage and quality controls in collaboration with engineering and security teams.
Build monitoring alerting and logging systems to ensure reliability and performance of data pipelines.
Collaborate with data scientists and analysts to deliver curated datasets for analytics and machine learning.
Automate workflow orchestration using Airflow Oozie or similar pipeline management tools.
Document system architecture schemas pipeline logic and operational processes for scalability and supportability.
Mentor junior engineers and contribute to engineering best practices and technical standards development.

Job Requirements

Candidates must hold a bachelor’s degree in computer science engineering or related technical fields.
Applicants should have at least five years of professional experience working with Hadoop based data systems.
Strong hands on expertise with Apache Spark in Scala Python or Java is required.
Solid experience with Hive HDFS Sqoop HBase and broader Hadoop ecosystem tools is essential.
Experience with Kafka Spark Streaming or Flink for real time data processing is required.
Strong SQL skills and experience working with relational and NoSQL databases are necessary.
Proficiency in workflow orchestration tools such as Airflow or Oozie is highly important.
Strong scripting skills in Python or shell scripting are required for automation tasks.
Understanding of distributed systems concepts including partitioning replication and fault tolerance is essential.
Experience with cloud based data platforms such as AWS EMR or Databricks is preferred.
Knowledge of modern lakehouse formats such as Delta Iceberg or Hudi is an advantage.

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Conclusion

This Hadoop Developer role offers strong opportunities for professionals seeking advanced data engineering careers in a fully remote environment. It combines big data processing distributed systems and modern analytics technologies within a high impact engineering team. Additionally, successful candidates will contribute to building scalable data platforms that support enterprise intelligence and innovation. Ultimately, experienced engineers looking to grow in modern data infrastructure and cloud ecosystems will find this role highly rewarding.

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