This role pays less than
89%
of similar roles. Most pay
$204,843–$278,000
— the shaded band above.
At the midpoint, this role pays about
$175k
versus about
$241k
for comparable roles.
Based on 240 similar postings.
Employer
About General Dynamics
General Dynamics is a global aerospace and defense company offering a broad portfolio of products and services in business aviation, ship construction, land combat vehicles, and information technology. It serves customers in the U.S. government, allied governments, and a diverse array of commercial markets.
General Dynamics currently has
1123 open roles
on FindRole.
Listed pay typically runs
$124,093–$150,385
across 984 roles with salary data.
The Director, Enterprise Data & Integration joins the GD Mission Systems team to establish and mature the organization's enterprise data capability. Reporting to the Chief Digital and Information Officer, you will lead a small Data Engineering team to transform fragmented, project-based initiatives into a scalable, governed, and sustainable enterprise asset. Your daily responsibilities include developing data strategies, architecture roadmaps, and governance frameworks while overseeing integration standards for analytics, reporting, and AI readiness. You will manage technical debt and modernize the integration landscape using tools such as MuleSoft Anypoint Platform, Snowflake, Microsoft Fabric, Azure Data Factory, Synapse, Databricks, Purview, and AWS data services. The role addresses the critical challenge of creating a unified, secure, and high-quality data infrastructure to support digital transformation and advanced information management across the organization's complex operational environment.
Develop and maintain the enterprise data strategy, roadmap, operating model, and target-state architecture.
Establish and mature enterprise data capabilities including governance, integration standards, and information management practices.
Define and govern enterprise data architecture, integration services, and reference models for scalable data pipelines.
Provide strategic leadership for enterprise data platforms, analytics environments, and AI-enabling technologies.
Lead, mentor, and provide technical direction to the Data Engineering team.
Evaluate technologies and vendors to ensure alignment with business objectives and long-term sustainability.
Reduce technical debt by eliminating platform fragmentation and unmanaged point-to-point integrations.
Establish governance processes and decision-making frameworks for all enterprise data and integration solutions.
What we're looking for
Bachelor's degree in Computer Science, Information Systems, Engineering, Data Management, or a related discipline.
10+ years of experience in enterprise data architecture, integration architecture, data engineering, or related disciplines.
Demonstrated experience developing enterprise data strategies, governance frameworks, architecture standards, and technology roadmaps.
Experience leading technical teams and influencing senior business and technology stakeholders.
Strong understanding of enterprise data management, integration, governance, analytics, cloud platforms, security, and information management principles.
Familiarity with AI/ML models and experience supporting digital transformation initiatives.
Preferred experience with MuleSoft Anypoint Platform and modern data platforms like Snowflake or Databricks.
Must be eligible to work in Canada and able to obtain and maintain a Canadian government security clearance.
Azure
Databricks
Synapse
Boomi
SQL Server
Azure Data Factory
Fivetran
REST
SOAP
APIs
XML
JSON
Python
JavaScript
NodeJS
Power BI
Excel
SFTP
JDBC/ODBC
Unity Catalog
Data Analysis
AI
Business Process Automation
Data Profiling
Data Engineering
Data Products
Workflow Automation
Integration Patterns
Analytics
Data Discovery
Solution Validation
Product Integration
Marketo
Salesforce
RingLead
MarTech
SaaS
Agile
Data Architecture
CRM
ERP
Data Warehouse
AI
Digital Transformation
Product Management
Data Governance
Marketing Analytics
Integration
Data Management
Data Architecture
Analytics
AI
Machine Learning
Master Data Management
Data Governance
Cloud Platforms
Business Intelligence
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Automation
GxP
NIST AI RMF
ISO 42001
Data Quality