Senior Data Engineer – Hadoop
Bright Vision Technologies- Location
- Austin NW / Domain, TX
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 145,000–165,000/yr
Posted yesterday
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.
Job Title
Senior Data Engineer - Hadoop
Location
100% Remote (U.S.)
Position Type
Full-time, Direct W2
Salary Range
$145,000–$165,000 Annually
Experience Required
6+ years
Sponsorship
U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
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. In this role you will be responsible for ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads. 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.
Required Qualifications
- 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.
Preferred Qualifications
- 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.
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to Harry@bvteck.com or contact us at (908)676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.Equal Employment Opportunity (EEO) Statement
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.
Skills
- Hadoop
- Machine Learning
- Spark
- Scala
- Python
- Java
- Hive
- HDFS
- HBase
- Kafka
- Flink
- SQL
- Airflow
- Shell
- EMR
- Azure
- Databricks
- Apache Iceberg
- Hudi
- Apache
- Kubernetes
- Trino
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