Manager, Data Architecture and Strategy; Hybrid

Eversource will not offer immigration-related sponsorship for this position (e.g., H-1B, O-1, J-1, TN, E-3, etc.). Applicants requiring visa sponsorship to start employment with Eversource will not be considered.

Eversource supports work-life balance by offering hybrid schedules for certain roles. Eligibility is based on job responsibilities, operational needs, nature of work and team dynamics. Current guidelines require employees to workat least three days in the office, including

Tuesdays and Wednesdays, with the third day set by the employee and supervisor based on department needs. These guidelines apply to roles approved for remote work and are subject to change, based on managerial discretion and work performance. All applicants must be able to work up to five days in the office if needed (for example: emergencies, training, or other business needs) or should the policy change.

The Data Architecture Manager leads the design, governance, and evolution of enterprise data architecture to enable scalable, reliable, and business-aligned data solutions. This role is accountable for the success of the enterprise data platform, ensuring data is structured, integrated, and accessible to drive analytics and decision-making. The manager oversees enterprise data architecture design, establishes and matures the enterprise data modeling practice, defines and enforces data domain standards, and ensures alignment with the broader enterprise architecture strategy and governance processes.

• Provide subject matter expertise on enterprise data management and analytics leading practices and ensure data assets are developed and delivered to meet business needs.
• Lead data architecture design and enable industry leading data engineering solutions and tools to help democratize data access across Eversource and enable AI/ML for business.
• Provide oversight to the data engineering teams, ensuring that data pipelines, transformations, and integrations are executed to align with the overall data architecture and governance framework.
• Enforce data governance processes and tools to simplify data access while ensuring data quality, literacy, and security.
• Collaborate with Enterprise and Solution Architects to ensure that Customer initiatives adhere to established data architecture principles and practices.
• Lead the design and implementation of enterprise data architecture for scalable, high-performing data solutions.
• Own and drive the overall success of the enterprise data platform, including performance, scalability, reliability, and maintainability.
• Own and drive the roadmap of the enterprise data platform, always collaborating with the data managers and stakeholders to ensure it meets business needs.
• Partner with business stakeholders, product teams, and engineering to translate business needs into effective data architecture solutions.
• Establish, evolve, and manage the enterprise data modeling practice, including conceptual, logical, and physical data models.
• Define and enforce enterprise data standards across domains, including data modeling, integration patterns, metadata, and governance practices.
• Ensure consistency, reuse, and interoperability of data assets across the enterprise.
• Collaborate with Enterprise and Solution Architects to align data architecture strategies and solutions with the enterprise architecture framework, standards, and roadmaps.
• Participate in architecture governance processes, including design reviews and strategic planning forums.
• Provide leadership, mentorship, and direction to data architects and related roles, drive ongoing learning to stay ahead of latest trends.
• Drive adoption of architectural best practices and promote a culture of accountability and continuous improvement.
• Identify and mitigate architectural risks and ensure long-term sustainability of data solutions

• Deep understanding of modern data architecture patterns (data lake, lake house, data warehouse, data mesh, medallion architecture)
• Ability to design scalable, secure and high-performing data ecosystems across structured and unstructured data.
• Expertise in conceptual, logical and physical data modeling
• Knowledge of integration patterns (CDC, streaming, APIs, event-driven architecture)
• Familiarity with tools such as Fivetran, informatica, Mule Soft, or similar platforms
• Experience with Databricks (preferred), Snowflake or similar analytics engines
• Understanding of storage, compute and cost…