Senior Data Engineer - AI-Driven Data Platform

Real Staffing; Minneapolis (MN); Hybrid; USD 140,000 - 170,000; Full time

Job summary

Real Staffing in Twin Cities is seeking a Senior Data Engineer to design and scale data pipelines that enable enterprise AI and analytics initiatives. You will work at the intersection of data engineering, cloud technologies, and business stakeholders.

The role emphasizes data quality, governance, and scalable solutions in a regulated environment with hybrid work options and close collaboration across cross-functional teams.

Qualifications

• Bachelor's or Master's in CS or a related field.
• 7+ years building production data solutions.
• Expert in data integration, transformation, and large-scale pipelines.
• Experienced with cloud-based data platforms and SQL on large datasets.
• Knowledge of governance, metadata, lineage, and quality controls.
• Experience in regulated enterprise environments.

Responsibilities

• Design and maintain scalable data pipelines from multiple systems.
• Build ingestion and processing for AI/Analytics initiatives.
• Ensure data reliability, governance, and accessibility across datasets.
• Define data quality standards and monitoring frameworks.
• Collaborate with architects and stakeholders to optimize data structure and usage.
• Support AI-enabled retrieval and knowledge management.
• Collaborate on cloud platform architecture and integration strategies.
• Drive automation and scalable engineering practices.
• Improve performance and testing of data solutions.

Skills

Data integration

Large-scale pipelines

Cloud data platforms

SQL analytics

Data governance

Problem solving

Education

Bachelor's or Master's in CS/Data Engineering

Tools

Cloud platforms

Vector databases

Data governance tools

Job description

Real Staffing in Twin Cities is seeking a Senior Data Engineer to design and scale data pipelines that enable enterprise AI and analytics initiatives. You will work at the intersection of data engineering, cloud technologies, and business stakeholders.

The role emphasizes data quality, governance, and scalable solutions in a regulated environment with hybrid work options and close collaboration across cross-functional teams.