AI Data Engineer – ML Data Pipelines

Job not on LinkedIn

🕒 July 27

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 29%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Empowers Staffing Inc

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2020

💼 Consulting

🎯 Recruiter

🤖 Artificial Intelligence

Consulting • Recruitment • Artificial Intelligence

Empowers Staffing Inc is presented in the provided content as (or appears to be represented by) a Minnesota-based IT consulting and staffing/ staff-augmentation provider. The webpage content largely corresponds to LAK Technology — a firm offering IT consulting and digital transformation services for small- to mid-size businesses, including software engineering (QA & testing, mobile apps, UI/UX, project management), data analytics and AI/ML, cloud migration and DevOps, custom solution development, and team extension/staff augmentation. The site lists a St. Paul, MN address and contact details and emphasizes workforce extension, bespoke software solutions, and data & cloud services.

📋 Description

• Design and build scalable data pipelines for ML workflows • Develop feature engineering and data preparation processes • Implement batch and real-time data ingestion systems • Ensure data quality, validation, and monitoring • Collaborate with ML engineers to support model training and deployment • Integrate pipelines with orchestration tools (Airflow or similar) • Optimize pipeline performance and cloud cost efficiency • Maintain documentation and version control of data workflows

🎯 Requirements

• 4+ years of experience in Data Engineering • Strong Python and SQL skills • Experience building data pipelines for ML or analytics systems • Hands-on experience with Spark, Databricks, or similar distributed processing frameworks • Experience with orchestration tools (Airflow or similar) • Experience in AWS, Azure, or GCP environments • Familiarity with data quality validation and monitoring frameworks • Understanding of feature engineering and model data lifecycle

🏖️ Benefits

• Remote work options