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

Location: Minnetonka Mills, MN

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 :

• Python

• SQL

• Spark

• Scala

• Azure

• AWS

• GCP

• Databricks

• Snowflake

• Synapse

• Fabric

Technical Requirements :

• Data Engineering, Data Platforms, or Analytics Engineering

• Experience building cloud-native data solutions

• 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

• Experience in enterprise-scale data ecosystems.