What are the responsibilities and job description for the AI/ML Data Engineering Architect :: onsite :: W2 Position position at Trebecon LLC?
Role: AI/ML Data Engineering Architect
Location: Minneapolis, MN (Onsite)
Role Overview
We are seeking a highly experienced AI/ML Data Engineering Architect to lead the design and delivery of enterprise-scale data and analytics solutions within the finance domain. This is a hands-on leadership role focused on building modern data platforms, driving AI/ML initiatives, and enabling advanced analytics capabilities across the organization.
The ideal candidate will bring strong expertise in data engineering, machine learning architecture, cloud technologies, and financial data analysis, along with the ability to collaborate effectively with senior business and technology stakeholders.
Key Responsibilities
- Design and architect scalable data platforms supporting AI/ML and advanced analytics initiatives.
- Lead end-to-end data engineering and analytics solution delivery in a hands-on capacity.
- Build and optimize enterprise data models, dimensional models, and data integration frameworks.
- Develop solutions leveraging Machine Learning, Deep Learning, NLP, and predictive analytics techniques.
- Architect data pipelines and data conformation strategies across multiple disparate data sources.
- Work closely with FP&A and finance stakeholders to support strategic reporting and analytics requirements.
- Design and optimize Snowflake-based data warehouse solutions and complex SQL processing frameworks.
- Provide technical leadership on Big Data, cloud-native architecture, and modern analytics ecosystems.
- Collaborate with executive leadership and cross-functional teams to drive data strategy and innovation.
- Ensure scalability, performance, governance, and reliability of enterprise data platforms.
Required Qualifications
- 15 years of overall IT experience with strong expertise in Data Engineering and Analytics.
- 8–10 years of experience designing enterprise data platform architectures with AI/ML capabilities.
- Strong experience with:
- SQL, PL/SQL, and complex query optimization
- Snowflake Data Warehouse
- Dimensional Modeling and Data Analysis
- Oracle databases
- Big Data technologies and modern data platforms
- Hands-on expertise in:
- Machine Learning
- Deep Learning
- Natural Language Processing (NLP)
- Time Series Analysis
- Linear and Non-linear Modeling
- Data Mining
- Optimization and Simulation techniques
- Experience designing data conformation and integration solutions across disparate enterprise systems.
- Minimum 3 years of experience working with AWS cloud technologies.
- Strong understanding of Finance and FP&A processes and analytics.
- Excellent communication and stakeholder management skills with experience working directly with senior executives.