Data Architect- Aerospace, Defense, and Mobility Sector - Senior Manager- Consulting - Open Location

EY•Hartford, DC

12d•$144,000 - $374,000

About The Position

EY is hiring a Senior Manager in Data Architecture for its consulting work in the aerospace, defense, automotive, and mobility sectors. The role focuses on crafting, deploying, and maintaining large-scale, AI-ready data architectures and helping clients use data to improve business outcomes. The successful candidate will lead technology projects and programs, solve complex analytical problems, and enable machine learning and AI at scale. The role includes client-facing work, relationship development, business development, and leadership of technical and non-technical teams. The Senior Manager will guide delivery against timelines, costs, quality, and risk, and apply Agile and Waterfall methods while coaching others and addressing technical constraints. The Data Architect will design and present data architecture solutions, lead junior colleagues, and sell and deliver technology consulting services. They will advise clients on digital transformation, data strategy, analytics technologies, industry trends, and business needs, including engagement with senior and C-level stakeholders. The position also leads data architecture and engineering teams, establishes governance practices, and collaborates across disciplines to deliver transactional, operational, analytical, and AI solutions. EY describes the role as open location, with work anywhere in the country.

Requirements

Bachelor’s degree in a STEM field.
12+ years of professional consulting experience in industry or technology consulting.
12+ years of hands-on experience architecting, designing, delivering, or optimizing data lake solutions.
5+ years of experience with native cloud products and services such as Azure or GCP.
8+ years of experience mentoring and leading data architect and data engineer teams.
In-depth knowledge of data architecture principles and best practices, including data modeling, data warehousing, data lakes, and data integration.
Demonstrated experience leading large data engineering teams to build platforms with complex architectures, diverse data flow patterns, relational and NoSQL databases, production-grade performance, and downstream delivery.
Hands-on experience designing end-to-end architectures and pipelines that collect, process, and reliably deliver data.
Proficiency in data modeling and selecting architectural patterns such as Data Fabrics, Data Mesh, Lake Houses, or Delta Lakes.
Previous hands-on coding skills in data engineering languages such as Python, Java, or Scala.
Ability to design horizontally and vertically scalable data solutions while optimizing performance.
Experience with Docker and container orchestration platforms such as Kubernetes for managing data workloads.
Experience with version control systems such as Git and knowledge of DevOps practices for automating data engineering workflows (DataOps).
Practical understanding of data encryption, access control, and security best practices for protecting sensitive data.
Excellent leadership, communication, and project management skills.
Knowledge of data security, database management, enterprise data management, metadata management, ontology design, and systems design.
Skills in applications integration, cloud computing and cloud architecture, data architecture design and modeling including Unified Namespace, data integration and quality, AI/Agentic AI-driven data operations including MCP, and physical AI and robotics simulation or implementation.
Experience delivering business use cases in Supply Chain or Finance.
Strong relationship management and business development skills.
Ability to build credibility as a trusted advisor with client senior decision makers and internal EY teams.
Ability to engage senior business leaders, shape goals, and align information and analytics requirements.
Ability to lead workshops and design sessions with clients, teams, and cross-functional partners.
Ability to communicate effectively with senior client stakeholders and constructively challenge them.

Nice To Haves

Master’s degree in Electrical or Mechanical Systems Engineering, Computer Science, Robotics, Statistics, Applied Mathematics, Data Science, or Machine Learning, or commensurate professional experience.
Experience working at a Big Four firm or a major manufacturer.
Experience with cloud data platforms such as Databricks.
Experience leading and influencing teams, with a focus on mentorship and professional development.
Passion for innovation and strategic application of emerging technologies to real-world challenges.
Ability to foster an inclusive environment that values diverse perspectives and empowers team members.
Skills in building and managing relationships, client trust and value, commercial astuteness, communicating with impact, and digital fluency.
Experience with automotive and aerospace sectors and consulting-company environments.

Responsibilities

Manage and deliver processes, solutions, and projects, emphasizing quality and effective risk management.
Drive continuous process improvement and identify solutions through research, analysis, and best practices.
Manage professional employees or supervise teams delivering complex technical initiatives; guide colleagues and recommend solutions to internal and external issues.
Design, architect, and present data architecture findings and solutions; lead junior team members and work with clients to sell and deliver technology consulting services.
Understand client problems and recommend methodologies and solutions related to data architectures, platforms, and technologies.
Help win new business for EY and serve as a trusted advisor to clients and prospects, including senior and C-level stakeholders.
Engage senior business leaders to understand and shape objectives, information needs, and analytics requirements.
Collaborate with data scientists, business analysts, IT teams, and other cross-functional partners to define data requirements, design solutions, and implement data strategies.
Organize and lead stakeholder workshops and design sessions to capture requirements, understand use cases and processes, brainstorm solutions, and align on architecture strategies and projects.
Lead the design and implementation of modern data architectures for transactional, operational, analytical, and AI solutions.
Direct and mentor global data architecture and engineering teams, fostering innovation, collaboration, and continuous improvement.
Establish data governance policies and practices, including security, quality, and lifecycle management.
Stay informed about industry trends and emerging data architecture and management technologies, and recommend improvements.
Manage complex data analysis, migration, and integration of enterprise solutions to modern platforms, including code efficiency and performance optimization.
Lead Infrastructure and Security engineers and architects in overall platform build.