Senior Data Engineering Delivery Manager -- Onsite -- Only W2 Profiles

Role : Senior Data Engineering Delivery Manager

Location : Minneapolis, MN – Onsite

Experience Required

15  Years Overall Experience


Key Responsibilities

• Lead the architecture, design, and implementation of enterprise AI/ML and data engineering solutions.

• Design scalable data platforms and analytics architectures using Snowflake, Oracle, SQL, and AWS cloud technologies.

• Develop and optimize complex SQL and PL/SQL queries, stored procedures, and performance tuning strategies.

• Build and maintain scalable data pipelines integrating disparate data sources for advanced analytics and reporting.

• Architect dimensional data models and data warehouses supporting enterprise analytics and FP&A functions.

• Collaborate with business stakeholders, finance teams, data scientists, and engineering teams to define data strategy and analytics solutions.

• Design AI/ML solutions involving:

• Machine Learning

• Deep Learning

• Natural Language Processing (NLP)

• Time Series Analysis

• Linear and Non-linear Modeling

• Data Mining

• Optimization and Simulation

• Lead data conformation and harmonization initiatives across multiple source systems.

• Provide technical leadership and hands-on delivery support throughout project lifecycles.

• Ensure data quality, governance, scalability, security, and performance standards are met.

• Work directly with senior executives and leadership teams to provide architecture recommendations and solution roadmaps.

• Mentor technical teams and establish best practices for AI/ML and data engineering implementations.

 

Experience Requirements

• 15  years of overall IT experience.

• 8–10 years of experience designing application/data architectures on enterprise data platforms using AI/ML technologies.

• 5  years of experience designing data conformation and integration solutions for analytics platforms.

• 3  years of hands-on experience working with AWS cloud technologies.

• Proven experience leading enterprise-scale data engineering and analytics programs.

• Finance domain experience is required.