Senior Data Engineer for AI/ML Pipelines

Quantum Technologies. LLC; Weehawken (NJ); On-site; USD 120,000 - 180,000; Full time

Job summary

Quantum Technologies LLC in Plano, TX seeks a data engineer with AI/ML experience to design scalable data pipelines and architectures. You will partner with data scientists to ensure data availability for ML models and drive data-driven decision making.

The role emphasizes ETL, data modeling, and cloud-based data warehousing with modern big data tools. Collaboration across teams and a strong focus on data quality are required.

Qualifications

• Bachelor’s degree or higher in CS, Engineering or data-related field.
• 7–10 years of data engineering experience with AI/ML focus.
• Experience designing scalable data pipelines and architectures.
• Proven ability to work with data scientists and stakeholders.
• Strong problem solving and communication skills.

Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures to support AI/ML applications.
• Collaborate with data scientists to understand data requirements and ensure data availability for ML models.
• Implement ETL processes to extract, transform, and load data into data warehouses and lakes.
• Optimize data storage and retrieval for performance and efficiency.
• Monitor and troubleshoot data pipeline performance and reliability.
• Ensure data quality and integrity through testing and validation.
• Document data engineering processes and communicate with cross-functional teams.

Skills

AI/ML Engineering

Python/Java/Scala

Data modeling

ETL/data warehousing

SQL/NoSQL databases

Cloud platforms

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

Hadoop

Spark

Kafka

PostgreSQL

MongoDB

AWS/Azure/GCP

Job description

Quantum Technologies LLC in Plano, TX seeks a data engineer with AI/ML experience to design scalable data pipelines and architectures. You will partner with data scientists to ensure data availability for ML models and drive data-driven decision making.

The role emphasizes ETL, data modeling, and cloud-based data warehousing with modern big data tools. Collaboration across teams and a strong focus on data quality are required.