Data Engineer – AI Platforms & Data Pipelines

Placements24; Riverton (UT); On-site; USD 95,000 - 135,000; Full time

Benefits offered by this job

Competitive salary

Annual bonus

Medical and retirement benefits

Growth opportunities

Generous PTO

Job summary

Placements24 is seeking a Data Engineer to build and maintain robust data platforms for AI initiatives in Utah. You will design, develop, and optimize pipelines to ingest, transform, and store large data volumes for machine learning and analytics.

The role focuses on data availability, quality, and accessibility to empower data science and AI teams to deploy cutting-edge solutions. 3–5 years of relevant experience is expected.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 3-5 years of data engineering experience.
• Proficiency in SQL and experience with relational and NoSQL databases.
• Strong programming skills in Python or Scala.
• Experience with big data technologies such as Spark or Hadoop.
• Familiarity with cloud data services (e.g., AWS Redshift, S3, Azure Data Lake, Google BigQuery).

Responsibilities

• Design, construct, install, test, and maintain highly scalable data management systems.
• Develop and optimize data pipelines for ETL.
• Collaborate with data scientists and AI engineers to understand data needs and provide reliable data solutions.
• Ensure data quality, integrity, and security across data platforms.
• Implement data warehousing solutions and data lakes to support analytical and AI workloads.
• Monitor and troubleshoot data infrastructure for performance and availability.

Skills

SQL

Python/Scala

Big data

Cloud services

Education

Bachelor's degree in CS/Engineering

Tools

Spark

Hadoop

NoSQL databases

Job description

Placements24 is seeking a Data Engineer to build and maintain robust data platforms for AI initiatives in Utah. You will design, develop, and optimize pipelines to ingest, transform, and store large data volumes for machine learning and analytics.

The role focuses on data availability, quality, and accessibility to empower data science and AI teams to deploy cutting-edge solutions. 3–5 years of relevant experience is expected.