Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global professional services organization is seeking a Data Architecture/Data Fabric Manager to support Resources and Utilities organizations in modernizing their data foundations, AI platforms, and governance models. The organization combines expertise in technology, cloud, data, AI, and industry-specific solutions to help clients transform business processes and improve operational outcomes.
The AI and Data practice focuses on applying advanced data engineering and AI capabilities to real-world enterprise challenges. The team develops trusted, production-grade data environments that enable analytics, artificial intelligence, automation, and improved decision-making across complex organizations.
The role requires a data architecture professional who can design enterprise data fabric solutions that provide unified, intelligent, and automated access to distributed data across on-premises and multi-cloud environments. The successful candidate will bring together data virtualization, active metadata, knowledge graphs, cataloging, and automated integration into a connected data layer that supports analytics and AI.
Key Responsibilities
- Architect enterprise data fabric solutions that provide unified, intelligent, and automated access to distributed data across on-premises and multi-cloud environments.
- Design connected data layers integrating data virtualization, active metadata, knowledge graphs, data cataloging, and automated data integration.
- Define enterprise reference architectures, integration patterns, and governance integration approaches that can scale across organizations.
- Enable self-service data consumption, data products, and real-time data delivery through enterprise data fabric environments.
- Apply modern data architecture concepts, including data mesh and data product approaches, to solve complex client challenges.
- Design and leverage cloud data platforms such as Snowflake, Databricks, Azure Synapse, and BigQuery.
- Incorporate streaming and API-based architectures into modern data solutions.
- Advise client architects and senior leaders on enterprise data modernization strategies.
- Shape technical solutions for major data modernization initiatives and pursuits.
- Develop scalable architectures that support analytics, artificial intelligence, and enterprise data products.
- Integrate governance, metadata, lineage, and data management capabilities into modern data architectures.
- Collaborate with cross-functional teams to ensure data solutions align with business objectives and technical requirements.
Required Qualifications
- Minimum of 7 years of experience in data architecture or enterprise data engineering.
- Minimum of 4 years of experience architecting data fabric solutions, including data virtualization, active metadata, knowledge graphs, and automated integration.
- Minimum of 4 years of experience working with cloud data platforms such as Snowflake, Databricks, Azure Synapse, or BigQuery.
- Minimum of 3 years of experience with data integration, ETL/ELT, metadata, and data lineage tooling.
- Minimum of 3 years of experience with API and streaming architectures.
- Minimum of 1 year of experience serving utilities clients in electric, gas, or water industries, or experience within utilities finance, controllership, or regulatory functions.
- Bachelor’s degree or equivalent experience with a minimum of 12 years of work experience.
- For candidates with an Associate’s degree, a minimum of 6 years of equivalent work experience is required.
- Strong understanding of enterprise data architecture, governance, integration, and cloud technologies.
- Ability to communicate complex technical concepts effectively with architects, executives, and business stakeholders.
Preferred Expertise
- Experience designing enterprise-scale data fabric architectures.
- Knowledge of data virtualization and active metadata technologies.
- Experience with knowledge graphs and enterprise data catalogs.
- Expertise in modern cloud data platforms and distributed data environments.
- Understanding of data mesh, data products, APIs, and real-time streaming architectures.
- Experience integrating data governance and lineage capabilities into enterprise architectures.
- Strong consulting, stakeholder management, and technical leadership capabilities.
- Experience working with utilities organizations and their unique operational, financial, and regulatory requirements.
Disclaimer
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