Hiring: W2 Candidates Only
Visa:Open to any visa typewith valid work authorization in the USA
Key Responsibilities:
- Design and implement scalable data ingestion and transformation pipelines using PySpark or Scala Hadoop Hive and Dremio.
- Build and manage Kafka batch pipelines for reliable data streaming and integration.
- Work with on-prem Hadoop ecosystems (Cloudera Hortonworks MapR) or cloud-native big data platforms.
- Develop and maintain RESTful APIs using Python (FastAPI Flask or Django) to expose data and services.
- Collaborate with data scientists ML engineers and platform teams to ensure seamless data flow and system performance.
- Monitor troubleshoot and optimize production data pipelines and services.
- Ensure security scalability and reliability across all data engineering components.
- (Optional but valuable) Contribute to the design and deployment of AI-driven RAG systems for enterprise use cases.
Required Skills & Qualifications
- Experience in Big Data Engineering.
- Strong hands-on experience with PySpark or Scala.
- Deep expertise in on-prem Hadoop distributions (Cloudera Hortonworks MapR) or cloud-based big data platforms.
- Proficiency in Kafka batch processing Hive and Dremio.
- Solid understanding of REST API development using Python frameworks.
- Familiarity with cloud platforms (Google Cloud Platform AWS or Azure).
- Experience or exposure to AI and RAG architectures is a plus.
- Excellent problem-solving communication and collaboration skills.
Hiring: W2 Candidates Only Visa:Open to any visa typewith valid work authorization in the USA Key Responsibilities: Design and implement scalable data ingestion and transformation pipelines using PySpark or Scala Hadoop Hive and Dremio. Build and manage Kafka batch pipelines for reliable data stre...
Hiring: W2 Candidates Only
Visa:Open to any visa typewith valid work authorization in the USA
Key Responsibilities:
- Design and implement scalable data ingestion and transformation pipelines using PySpark or Scala Hadoop Hive and Dremio.
- Build and manage Kafka batch pipelines for reliable data streaming and integration.
- Work with on-prem Hadoop ecosystems (Cloudera Hortonworks MapR) or cloud-native big data platforms.
- Develop and maintain RESTful APIs using Python (FastAPI Flask or Django) to expose data and services.
- Collaborate with data scientists ML engineers and platform teams to ensure seamless data flow and system performance.
- Monitor troubleshoot and optimize production data pipelines and services.
- Ensure security scalability and reliability across all data engineering components.
- (Optional but valuable) Contribute to the design and deployment of AI-driven RAG systems for enterprise use cases.
Required Skills & Qualifications
- Experience in Big Data Engineering.
- Strong hands-on experience with PySpark or Scala.
- Deep expertise in on-prem Hadoop distributions (Cloudera Hortonworks MapR) or cloud-based big data platforms.
- Proficiency in Kafka batch processing Hive and Dremio.
- Solid understanding of REST API development using Python frameworks.
- Familiarity with cloud platforms (Google Cloud Platform AWS or Azure).
- Experience or exposure to AI and RAG architectures is a plus.
- Excellent problem-solving communication and collaboration skills.
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