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

About the role

EY is seeking a Senior 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.
• Be face to face with external clients and build new and existing relationships in the sector.
• Apply your depth of expertise to guide others and interpret internal/external issues to recommend quality solutions.
• Provide assurance to leadership by managing 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.

Requirements

• A Bachelor’s degree required in STEM.
• 12+ years professional consulting experience in industry or in technology consulting.
• 12+ years hands-on experience in architecting, designing, delivering or optimizing data lake solutions.
• 5+ years’ experience with native cloud products and services such as Azure or GCP.
• 8+ 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.
• Demonstrated experience in leading large data engineering teams to design and build platforms with complex architectures and diverse features including various data flow patterns, relational and no-SQL databases, production-grade performance, and delivery to downstream use cases and applications.
• 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

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.
• Building and Managing Relationships
• Client Trust and Value and Commercial Astuteness
• Communicating With Impact and Digital Fluency

Benefits

To qualify for the role, you must have:

• A Bachelor’s degree required in STEM.
• 12+ years professional consulting experience in industry or in technology consulting.
• 12+ years hands-on experience in architecting, designing, delivering or optimizing data lake solutions.
• 5+ years’ experience with native cloud products and services such as Azure or GCP.
• 8+ 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.
• Demonstrated experience in leading large data engineering teams to design and build platforms with complex architectures and diverse features including various data flow patterns, relational and no-SQL databases, production-grade performance, and delivery to downstream use cases and applications.
• 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

The base salary range for this job in all geographic locations in the US is $144,000 to $329,100. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $172,800 to $374,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.

Schedule

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.

Application Instructions

We are looking for top performers who demonstrate a blend of technical expertise and business acumen, with the ability to build strong client relationships and lead teams through change. Emotional agility and hybrid collaboration skills are key to success in this dynamic role.