Plano Data Engineer: AI/ML Pipelines & ETL

Ethereum Technologies; Weehawken (NJ); On-site; USD 90,000 - 140,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Job summary

Ethereum Technologies in Plano, TX is seeking a senior Data Engineer with a strong AI/ML background to design and maintain scalable data pipelines and architectures for advanced analytics and machine learning projects.

The role emphasizes collaboration with data scientists, ETL implementation, and ensuring data quality across data warehouses and lakes. Strong cloud and big data tech experience is required.

Qualifications

• 7–10 years of data engineering experience with AI/ML focus.
• Strong data modeling, ETL, and data warehousing knowledge.
• Experience designing scalable data pipelines for analytics/ML.
• Proficiency in Python, Java, or Scala and SQL/NoSQL databases.
• Hands-on with Hadoop/Spark/Kafka and cloud data services.

Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures for AI/ML.
• Collaborate with data scientists to ensure data availability for models.
• Implement ETL to move data into data warehouses and lakes.
• Optimize storage and retrieval for performance and cost.
• Monitor pipeline reliability, quality, and testing.
• Document processes and communicate with cross-functional teams.
• Keep up-to-date with data engineering and AI/ML trends.

Skills

AI/ML Engineering

Python

Java

Scala

SQL

NoSQL

PostgreSQL

MySQL

Hadoop

Spark

Kafka

Cloud</wbr>Platform

Data warehousing

ETL

TensorFlow

PyTorch

Scikit-learn

Education

Bachelor's degree in CS/Engineering/Data Science

Master's degree preferred

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

Azure

Google Cloud

Hadoop

Spark

Kafka

PostgreSQL

MongoDB

Job description

Ethereum Technologies in Plano, TX is seeking a senior Data Engineer with a strong AI/ML background to design and maintain scalable data pipelines and architectures for advanced analytics and machine learning projects.

The role emphasizes collaboration with data scientists, ETL implementation, and ensuring data quality across data warehouses and lakes. Strong cloud and big data tech experience is required.