Remote AI-Enabled Enterprise Data Architect & Analytics Lead

Barnes Group; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

HSA with company contributions

401(k) with company matching

Job summary

Barnes Aerospace is seeking an experienced Enterprise Data Products & AI Analytics Architect to lead the strategy, architecture, and delivery of enterprise data products and AI-enabled analytics. You will own the end-to-end data product lifecycle, define enterprise Power BI architecture and standards, and drive the organization’s AI-powered analytics strategy.

This hands-on leadership role requires deep expertise in data engineering, enterprise architecture, BI, and modern analytics technologies

Qualifications

• Bachelor's degree in CS, Engineering, IS, Data Science, or related field.
• 12+ years of experience in data engineering, enterprise data architecture, analytics engineering, or business intelligence.
• 5+ years of technical leadership designing and delivering enterprise-scale data platforms and data products.
• Deep expertise with Azure Data Factory, Azure Databricks, Azure Data Lake, SQL, Python, PySpark, Spark SQL, and Delta Lake.
• Proven experience implementing Medallion Architecture and integrating data across multiple ERP and enterprise systems.
• Strong experience with data modeling, Power BI semantic models, DAX, enterprise reporting architecture, and performance optimization.
• Experience implementing data quality, governance, observability, lineage, monitoring, and metadata management frameworks.
• Experience with AI-enabled analytics, Power BI Copilot, Databricks Genie, conversational BI, or similar technologies.
• Knowledge of Azure DevOps, Git, CI/CD, and DataOps best practices.
• Strong communication, stakeholder management, and business acumen with the ability to translate business requirements into scalable technical solutions.
• Preferred: Aerospace, manufacturing, industrial, or multi-site ERP environments.

Responsibilities

• Own the architecture, standards, and roadmap for enterprise data products and analytics solutions.
• Lead data integration, ingestion, transformation, and modeling across Azure, Databricks, and multiple ERP environments using Medallion Architecture.
• Establish enterprise standards for data quality, governance, observability, lineage, certification, and master data management.
• Define and optimize the Power BI semantic layer, including KPI governance, business logic, calculations, aggregations, and self-service analytics capabilities.
• Drive AI for BI strategy, including AI-enabled analytics, conversational BI, natural language querying, and AI-assisted dashboard development.
• Develop reusable data models, standardized business definitions, and certified datasets that support enterprise reporting and decision-making.
• Establish engineering best practices, DataOps/CI-CD frameworks, and architectural governance standards.
• Provide hands-on technical leadership, solution design, code reviews, troubleshooting, and performance optimization.
• Collaborate with business stakeholders, IT teams, and external partners to deliver scalable, business-focused analytics solutions.

Skills

Data engineering

Enterprise data architecture

Analytics engineering

Business intelligence

Leadership

Stakeholder management

Communication

AI/ML analytics

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field

Tools

Azure Data Factory

Azure Databricks

Azure Data Lake

SQL

Python

PySpark

Spark SQL

Delta Lake

Power BI

Power BI Copilot

Databricks Genie

Git

Azure DevOps

CI/CD

Job description

Barnes Aerospace is seeking an experienced Enterprise Data Products & AI Analytics Architect to lead the strategy, architecture, and delivery of enterprise data products and AI-enabled analytics. You will own the end-to-end data product lifecycle, define enterprise Power BI architecture and standards, and drive the organization’s AI-powered analytics strategy.

This hands-on leadership role requires deep expertise in data engineering, enterprise architecture, BI, and modern analytics technologies