Data Architect - Power & Utilities - Manager - Consulting - Location OPEN

About the role

EY is seeking a Manager with solid experience in the utilities sector to serve as a Data Architect. The ideal candidate will have a history of working for consulting companies and be well-versed in the fast-paced culture of consulting work. This role is dedicated to the utilities sector, where the successful candidate will craft, deploy, and maintain large-scale AI data ready architectures.

Responsibilities

• Help our clients enable better business outcomes while working in the rapidly growing Power & Utilities sector.
• Lead and develop your skill set to keep up with the ever-growing demands of the modern data platform.
• Solve complex analytical problems to bring data to insights and enable the use of ML and AI at scale for your clients.
• Lead transformative technology projects and programs that align with our organizational strategy to achieve impactful outcomes.
• Manage timelines, costs, and quality, and lead both technical and non-technical project teams in the development and implementation of cutting-edge technology solutions and infrastructure.
• Manage complex data analysis, migration, and integration of enterprise solutions to modern platforms, including code efficiency and performance optimizations.
• Design data solutions that can scale horizontally and vertically while optimizing performance.
• Manage professional employees or supervising team members to deliver complex technical initiatives.

Requirements

• A Bachelor’s degree required in STEM.
• 8+ years professional consulting experience in industry or in technology consulting.
• 8+ years hands-on experience in architecting, designing, delivering or optimizing data lake solutions.
• 3+ years’ experience with native cloud products and services such as Azure or GCP.
• 5+ years of experience mentoring and leading teams of data architects and data engineers, fostering a culture of innovation and professional development.
• In-depth knowledge of data architecture principles and best practices, including data modelling, data warehousing, data lakes, and data integration.
• Hands-on experience in designing end-to-end architectures and pipelines that collect, process, and deliver data to its destination efficiently and reliably.
• Proficiency in data modelling techniques and the ability to choose appropriate architectural design patterns, including Data Fabrics, Data Mesh, Lake Houses, or Delta Lakes.
• Previous hands-on coding skills in languages commonly used in data engineering, such as Python, Java, or Scala.
• Experience with containerization technologies like Docker and container orchestration platforms like Kubernetes for managing data workloads.
• Experience in version control systems (e.g. Git) and knowledge of DevOps practices for automating data engineering workflows (DataOps).
• Practical understanding of data encryption, access control, and security best practices to protect sensitive data.
• Experience leading Infrastructure and Security engineers and architects in overall platform build.
• Excellent leadership, communication, and project management skills.

Qualifications

• A Master’s degree in Electrical / Power Systems Engineering, Computer science, Statistics, Applied Mathematics, Data Science, Machine Learning or commensurate professional experience.
• Experience working at big 4 or a major utility.
• Experience with cloud data platforms like Databricks.
• Experience in leading and influencing teams, with a focus on mentorship and professional development.
• A passion for innovation and the strategic application of emerging technologies to solve real-world challenges.
• The ability to foster an inclusive environment that values diverse perspectives and empowers team members.

Skills

• Technical Skills: Applications Integration, Cloud Computing and Cloud Computing Architecture, Data Architecture Design and Modelling, Data Integration and Data Quality, AI/Agentic AI driven data operations.
• Business Skills: Become a trusted advisor to your clients’ senior decision makers and internal EY teams by establishing credibility and expertise in both data strategy in general and in the use of analytic technology solutions to solve business problems.
• Collaboration: Engage with senior business leaders to understand and shape their goals and objectives and their corresponding information needs and analytic requirements.
• Client Engagement: Collaborate with cross-functional teams (Data Scientists, Business Analysts, and IT teams) to define data requirements, design solutions, and implement data strategies that align with our clients’ objectives.
• Workshops and Design Sessions: Organize and lead workshops and design sessions with stakeholders, including clients, team members, and cross-functional partners, to capture requirements, understand use cases, personas, key business processes, brainstorm solutions, and align on data architecture strategies and projects.
• Data Architecture Leadership: Lead the design and implementation of modern data architectures, supporting transactional, operational, analytical, and AI solutions.
• Team Management: Direct and mentor global data architecture and engineering teams, fostering a culture of innovation, collaboration, and continuous improvement.
• Data Governance: Establish data governance policies and practices, including data security, quality, and lifecycle management.
• Industry Trends: Stay abreast of industry trends and emerging technologies in data architecture and management, recommending innovations and improvements to enhance our capabilities.

Benefits

To qualify for the role, you must have:

• A Bachelor’s degree required in STEM.
• 8+ years professional consulting experience in industry or in technology consulting.
• 8+ years hands-on experience in architecting, designing, delivering or optimizing data lake solutions.
• 3+ years’ experience with native cloud products and services such as Azure or GCP.
• 5+ years of experience mentoring and leading teams of data architects and data engineers, fostering a culture of innovation and professional development.
• In-depth knowledge of data architecture principles and best practices, including data modelling, data warehousing, data lakes, and data integration.
• Hands-on experience in designing end-to-end architectures and pipelines that collect, process, and deliver data to its destination efficiently and reliably.
• Proficiency in data modelling techniques and the ability to choose appropriate architectural design patterns, including Data Fabrics, Data Mesh, Lake Houses, or Delta Lakes.
• Manage complex data analysis, migration, and integration of enterprise solutions to modern platforms, including code efficiency and performance optimizations.
• Previous hands-on coding skills in languages commonly used in data engineering, such as Python, Java, or Scala.
• Ability to design data solutions that can scale horizontally and vertically while optimizing performance.
• Experience with containerization technologies like Docker and container orchestration platforms like Kubernetes for managing data workloads.
• Experience in version control systems (e.g. Git) and knowledge of DevOps practices for automating data engineering workflows (DataOps).
• Practical understanding of data encryption, access control, and security best practices to protect sensitive data.
• Experience leading Infrastructure and Security engineers and architects in overall platform build.
• Excellent leadership, communication, and project management skills.
• Data Security and Database Management, Enterprise Data Management and Metadata Management, Ontology Design and Systems Design.

Pay

Individual salaries within the range of $125,500 to $230,200 USD are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

Schedule

Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.