Data Engineer – AI/ML & Advanced Analytics

Quantum Technologies LLC; Minnetonka (MN); On-site; USD 80,000 - 107,000; Full time

Job summary

Quantum Technologies LLC seeks a skilled Data Engineer to support enterprise AI/ML and Advanced Analytics initiatives by building scalable, reliable, and high-performance data platforms and pipelines. This role focuses on designing and engineering modern data solutions that enable machine learning and analytics-driven decision making.

The candidate will design and maintain data lakehouse architectures, implement data governance, and collaborate with data scientists to optimize feature

Qualifications

• Experience in data engineering and analytics platforms.
• Experience with ETL/ELT frameworks and large-scale data processing.
• Knowledge of distributed data processing technologies and modern data architectures.
• Experience with data lake, warehouse, and lakehouse platforms.
• Understanding of data governance, security, and data quality practices.
• Experience supporting AI/ML platforms and Data Science workloads.
• Familiarity with feature stores, MLOps, and model deployment pipelines.
• Experience with real-time streaming technologies.

Responsibilities

• Design, develop, and maintain scalable data pipelines supporting AI/ML and analytics workloads.
• Build and optimize batch and real-time data ingestion frameworks.
• Develop data integration solutions across multiple internal and external data sources.
• Engineer reliable datasets and feature stores that support machine learning model development.
• Implement data transformation, cleansing, enrichment, and validation processes.
• Design and maintain modern data lake, lakehouse, and data warehouse architectures.
• Ensure data quality, integrity, security, and governance standards are met.
• Optimize data processing performance, scalability, and operational efficiency.
• Collaborate with Data Scientists and Analysts to support feature engineering and model deployment requirements.
• Enable MLOps and ML platform capabilities to support model operationalization.
• Implement monitoring, observability, and operational support processes for data platforms.
• Maintain documentation, data lineage, and metadata management standards.
• Strong collaboration and problem-solving skills.
• Build scalable, reliable, and high-performance data solutions.
• Design and optimize cloud-native architectures supporting AI and analytics.
• Develop robust ingestion, transformation, and orchestration frameworks.
• Create data foundations that accelerate machine learning and advanced analytics.
• Ensure trusted, secure, and compliant enterprise data assets.
• Drive reliability, scalability, monitoring, and maintainability across data platforms.
• Builds scalable data ecosystems that power analytics and AI initiatives.
• Ensures data is accessible, trusted, and ready for advanced analytics.
• Partners effectively with Data Scientists, Architects, and Product teams.
• Improves performance, reliability, and efficiency of data platforms.
• Enables faster insight generation and AI innovation.
• Delivers robust engineering solutions that create measurable business value.

Skills

Data Engineering

ETL/ELT

Distributed Data Processing

AI/ML Platforms

MLOps

Real-time Streaming

Tools

Data Lake

Data Warehouse

Lakehouse

Feature Stores

Job description

Data Engineer – AI/ML & Advanced Analytics

Location:

Duration:

12Months+ Extension

Domain Exposure:

Manufacturing

Client:

To Be Discussed Later

Employment Type:

W-2, 1099, C2C

Work Authorization:

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title:Data Engineer – AI/ML & Advanced Analytics

Duration: 12 Months + Extension

Bill Rate: $68/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Summary

We are seeking a highly skilled Data Engineer to support enterprise AI/ML and Advanced Analytics initiatives by building scalable, reliable, and high-performance data platforms and pipelines. This role will focus on designing and engineering modern data solutions that enable machine learning, advanced analytics, and AI-driven decision making.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines supporting AI/ML and analytics workloads.
• Build and optimize batch and real-time data ingestion frameworks.
• Develop data integration solutions across multiple internal and external data sources.
• Engineer reliable datasets and feature stores that support machine learning model development.
• Implement data transformation, cleansing, enrichment, and validation processes.
• Design and maintain modern data lake, lakehouse, and data warehouse architectures.
• Ensure data quality, integrity, security, and governance standards are met.
• Optimize data processing performance, scalability, and operational efficiency.
• Collaborate with Data Scientists and Analysts to support feature engineering and model deployment requirements.
• Enable MLOps and ML platform capabilities to support model operationalization.
• Implement monitoring, observability, and operational support processes for data platforms.
• Maintain documentation, data lineage, and metadata management standards.
• Strong collaboration and problem-solving skills.
• Build scalable, reliable, and high-performance data solutions.
• Design and optimize cloud-native architectures supporting AI and analytics.
• Develop robust ingestion, transformation, and orchestration frameworks.
• Create data foundations that accelerate machine learning and advanced analytics.
• Ensure trusted, secure, and compliant enterprise data assets.
• Drive reliability, scalability, monitoring, and maintainability across data platforms.
• Builds scalable data ecosystems that power analytics and AI initiatives.
• Ensures data is accessible, trusted, and ready for advanced analytics.
• Partners effectively with Data Scientists, Architects, and Product teams.
• Improves performance, reliability, and efficiency of data platforms.
• Enables faster insight generation and AI innovation.
• Delivers robust engineering solutions that create measurable business value.

Required Skills

Technical Requirements

• Data Engineering, Data Platforms, or Analytics Engineering
• Experience with ETL/ELT frameworks and large-scale data processing
• Knowledge of distributed data processing technologies and modern data architectures
• Experience with data lake, warehouse, and lakehouse platforms
• Understanding of data governance, security, and data quality practices
• Experience supporting AI/ML platforms and Data Science workloads
• Familiarity with feature stores, MLOps, and model deployment pipelines
• Experience with real-time streaming technologies

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.