Remote AI/ML Data Engineer for Scalable Pipelines

Placements24; Riverton (UT); Remote; USD 90,000 - 150,000; Full time

Job summary

Placements24 is seeking an AI/ML Data Engineer to design, build, and maintain scalable data solutions that power AI initiatives. This fully remote role enables you to work from anywhere while collaborating with data scientists, ML engineers and software developers to ensure data is accessible and reliable.

You will develop robust data pipelines, ETL/ELT processes, data warehousing and data lake solutions, and implement governance and security best practices.

Qualifications

• Bachelor's degree in CS, Engineering, or related quantitative field.
• Proven Data Engineer with track record of building analytics/ML data pipelines.
• Strong Python or Scala programming skills.
• Experience with Spark/Hadoop and other big data tech.
• Experience with AWS, Azure, or GCP data services and cloud data warehousing.

Responsibilities

• Design, build, and maintain scalable data pipelines for AI/ML apps.
• Develop ETL/ELT processes to ingest, transform, and load data.
• Ensure data quality, integrity, and availability for downstream use.
• Optimize storage and processing for performance and cost.
• Implement data governance and security best practices.
• Collaborate with data scientists and ML engineers on data needs.
• Develop and manage data warehousing and data lake solutions.
• Monitor pipeline performance and troubleshoot issues.

Skills

SQL

Python

Scala

Big data

Spark

Hadoop

AWS

Azure

GCP

Data governance

Data warehousing

ETL/ELT tools

Education

Bachelor's degree in CS/Engineering or related field

Tools

ETL/ELT tools

Relational and NoSQL databases

Job description

Placements24 is seeking an AI/ML Data Engineer to design, build, and maintain scalable data solutions that power AI initiatives. This fully remote role enables you to work from anywhere while collaborating with data scientists, ML engineers and software developers to ensure data is accessible and reliable.

You will develop robust data pipelines, ETL/ELT processes, data warehousing and data lake solutions, and implement governance and security best practices.