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Ernst & Young

Global professional services: consulting, assurance, tax

Data Architect Senior Manager - Defense, Mobility Sector

Data ManagementConfirmed live in the last 24 hours
Full-timeRemote in USA$144k - $374k

About the Job

Requirements

  • A bachelor's degree in STEM is required.
  • At least 12 years of professional consulting experience in industry or technology consulting is required.
  • At least 12 years of hands-on experience architecting, designing, delivering, or optimizing data lake solutions is required.
  • At least 5 years of experience with native cloud products and services such as Azure or Google Cloud Platform is required.
  • At least 8 years of experience mentoring and leading teams of data architects and data engineers is required.
  • In-depth knowledge of data architecture principles and best practices, including data modelling, data warehousing, data lakes, and data integration, is required.
  • Demonstrated experience leading large data engineering teams to design and build platforms with complex architectures and diverse features, including various data flow patterns, relational and NoSQL databases, production-grade performance, and delivery to downstream use cases and applications, is required.
  • Hands-on experience designing end-to-end architectures and pipelines that collect, process, and deliver data efficiently and reliably is required.
  • Proficiency in data modelling techniques and the ability to choose architectural design patterns, including Data Fabrics, Data Mesh, Lake Houses, or Delta Lakes, is required.
  • Experience managing complex data analysis, migration, and integration of enterprise solutions to modern platforms, including code efficiency and performance optimization, is required.
  • Previous hands-on coding skills in commonly used data engineering languages such as Python, Java, or Scala are required.
  • Ability to design data solutions that scale horizontally and vertically while optimizing performance is required.
  • Experience with containerization technologies such as Docker and orchestration platforms such as Kubernetes for managing data workloads is required.
  • Experience with version control systems such as Git and knowledge of DevOps practices for automating data engineering workflows (DataOps) are required.
  • Practical understanding of data encryption, access control, and security best practices for protecting sensitive data is required.
  • Experience leading infrastructure and security engineers and architects in an overall platform build is required.
  • Experience with application integration, cloud computing and cloud architecture, data architecture design and modelling, Unified Namespace, data integration and quality, AI- and Agentic AI-driven data operations, and MCP is required.
  • Experience with physical AI and robotics simulation or implementation is required.
  • Experience delivering business use cases in supply chain or finance is required.
  • Data security, database management, enterprise data management, metadata management, ontology design, and systems design skills are required.
  • Strong relationship management and business development skills are required.
  • Ability to establish credibility as a trusted advisor to senior client decision makers and internal teams in data strategy and analytic technology solutions is required.
  • Ability to engage senior business leaders to shape goals, objectives, information needs, and analytic requirements is required.
  • Ability to collaborate with data scientists, business analysts, and IT teams to define data requirements, design solutions, and implement data strategies is required.
  • Ability to organize and lead stakeholder workshops and design sessions to capture requirements, understand use cases, personas, and business processes, brainstorm solutions, and align on data architecture strategies and projects is required.
  • Excellent leadership, communication, and project management skills are required.

Responsibilities

  • Design, architect, and present findings and solutions for data architecture problems.
  • Lead junior team members and work with clients to sell and deliver technology consulting services.
  • Serve as a resource for understanding client problems and responding with methodologies and solutions involving data architectures, platforms, and technologies.
  • Help win new business for EY and advise clients on digital transformation, analytic technology, industry trends, and client motivations.
  • Manage the delivery of processes, solutions, and projects, focusing on quality and risk management.
  • Drive continuous process improvement and identify innovative solutions through research, analysis, and best practices.
  • Manage professional employees or supervise team members delivering complex technical initiatives, applying expertise to guide others and recommend solutions to internal and external issues.
  • Lead transformative technology projects and programs aligned with organizational strategy, managing timelines, costs, and quality.
  • Lead technical and non-technical project teams in developing and implementing technology solutions and infrastructure.
  • Coach others and propose solutions to technical constraints using project and program delivery methods, including Agile and Waterfall.
  • Build new and existing relationships with clients in the sector.
  • Engage with clients and prospects at the C-suite level and constructively challenge them.
  • Collaborate with cross-functional teams to define data requirements, design solutions, and implement client-aligned data strategies.
  • Lead workshops and design sessions with stakeholders to capture requirements, clarify use cases and processes, and align on architecture strategies and projects.
  • Lead the design and implementation of modern data architectures supporting 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 data security, quality, and lifecycle management.
  • Monitor industry trends and emerging technologies in data architecture and management, recommending innovations and improvements.

Desired Qualifications

  • A master's degree in Electrical Engineering, Mechanical 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.
  • Interest in applying 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.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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