Data and Analytics AI Engineer

AAON•Tulsa, OK

1d•Onsite

About The Position

The Data and Analytics AI Engineer is responsible for designing, building, and supporting enterprise data, analytics, automation, and artificial intelligence solutions that enable business growth and operational excellence. This role serves as the technical bridge between business requirements and modern data platforms, delivering scalable data pipelines, database and reporting solutions, enterprise application integrations, and intelligent automation capabilities. The individual will work closely with business stakeholders, analysts, and application teams to develop integrated solutions leveraging SQL Server, cloud technologies, data engineering best practices, and modern analytics and AI platforms. The ideal candidate combines deep expertise in databases, integration, and business intelligence with a strong understanding of data modeling, ETL processes, reporting, and data governance.

Requirements

Bachelor's degree in Computer Science, Mathematics, Information Systems, Data Science, or related field, or relevant experience.
10+ years of experience in data development, database administration, business intelligence, or enterprise integration roles.
Expert-level proficiency in SQL Server and T-SQL; experience with Oracle or other relational database platforms.
Proven experience developing and supporting large portfolios of enterprise application integrations, both internal and with third-party providers.
Hands-on experience with BI and reporting platforms (e.g., SSRS, Power BI, Tableau).
Experience supporting ERP and CRM platforms (e.g., Microsoft Dynamics), including migration and consolidation projects.
Proficiency in one or more programming languages (e.g., C#, Python).
Experience with data governance, security, and audit compliance practices.
Working knowledge of cloud platforms (Azure preferred) and modern data architectures.
Strong analytical thinking, problem-solving, and communication skills.
Attention to detail and data accuracy
Systems thinking and technical leadership
Effective communication with technical and non-technical stakeholders
Business partnership and customer focus
Time management and project coordination
Continuous learning and adaptability

Nice To Haves

Experience with Microsoft Fabric, Azure Data Factory, or data lake/lakehouse architectures.
Experience with Python and Spark/PySpark for large-scale data processing.
Exposure to generative AI technologies (e.g., Azure OpenAI, Copilot Studio, retrieval-augmented generation, AI agents).
Experience with Power Platform and Power Automate workflow development.
Experience with CI/CD pipelines and version control tools (e.g., Git, Azure DevOps).
Microsoft Azure, Fabric, or Power Platform certifications.
Experience supporting manufacturing or industrial operations.
Experience leading, managing, or mentoring technical teams.

Responsibilities

Design, develop, and maintain enterprise data pipelines, data models, and integrations across ERP, CRM, HR, finance, and manufacturing systems.
Build and optimize ETL/ELT processes for efficient data ingestion, transformation, and storage.
Develop, monitor, and support a portfolio of integrations between internal systems and external providers.
Lead data migration and consolidation efforts to modernize or retire legacy applications.
Architect, administer, and optimize SQL Server and other relational database environments supporting enterprise applications.
Ensure database performance, reliability, security, and availability across platforms.
Support audit and compliance activities, including evidence gathering and controls documentation (e.g., SOX).
Develop enterprise reporting and dashboards using Power BI, SSRS, and related tools.
Partner with business units to define KPIs, gather requirements, and translate them into technical specifications.
Build self-service BI capabilities and optimize datasets, semantic models, and reporting performance.
Identify opportunities to eliminate manual processes through automation using Power Automate and related technologies.
Support development and deployment of AI, machine learning, and generative AI solutions as the enterprise platform matures.
Evaluate emerging AI and automation technologies and recommend adoption opportunities.
Support the Azure Data Platform, Microsoft Fabric, and related cloud data services.
Implement security, identity and access management, and compliance requirements.
Develop technical documentation, data lineage, and operational runbooks.
Collaborate with business leaders to understand strategic objectives and translate them into technical solutions.
Mentor analysts and junior engineers and participate in architecture and governance reviews.