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About the Role
We are seeking an experienced Senior Data Engineer - Hadoop to design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related big-data ecosystems. This role involves ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads. The ideal candidate will possess deep technical expertise across the Hadoop ecosystem, strong software engineering fundamentals, and a clear understanding of delivering reliable, performant, and cost-effective data platforms.
Responsibilities
- 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.
- Support enterprise analytics, machine learning, and reporting workloads.
- 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.
- Experience operating Hadoop on cloud platforms such as AWS EMR, Azure HDInsight, or Databricks.
- Familiarity with modern lakehouse formats (Delta, Iceberg, Hudi).
- Exposure to data governance tooling such as Apache Atlas or Collibra.
- Experience with Kubernetes-based data platforms (Spark-on-K8s, Trino).
- Hands-on experience with CI/CD and infrastructure-as-code in data engineering workflows.
Skills
- Hadoop
- Apache Spark
- Scala
- Python
- Java
- Hive
- HDFS
- Sqoop
- HBase
- Kafka
- Spark Streaming
- Flink
- SQL
- NoSQL
- Airflow
- Oozie
- Shell scripting
- AWS EMR
- Azure HDInsight
- Databricks
- Delta Lake
- Iceberg
- Hudi
- Apache Atlas
- Collibra
- Kubernetes
- Trino
- CI/CD
- Infrastructure-as-code
Location
- 100% Remote (U.S.)
Work Type
- Full-time
- Direct W2
Experience Level
- 6+ years
- Five or more years of professional experience
Education Level
- Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
Salary/Compensations
- $145,000–$165,000 Annually
About the Company
- Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
- This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Equal Opportunity
- Bright Vision Technologies is an Equal Opportunity Employer.
- Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws.
- This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
- BV Teck expressly prohibits any form of workplace harassment or discrimination.
- Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.