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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead, Data Architect - **Company:** FRACTAL LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $130,000.0 - $185,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Computing Platforms, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Data Architecture, Data Infrastructure, Data Security, Data Systems, Data Vault Modeling, Data Warehousing, Relational Databases, Software Design Patterns, Dimensional Modeling, Distributed Computing Environment, Information Lifecycle Management, Logical Data Models, Machine Learning, NoSQL, Performance Tuning, Data Mesh, SQL Databases, Data Streaming, Enterprise Data Management, Data Processing, Google Cloud, Data Ingestion, Azure Data Factory, Large Language Models, Snowflake, Multi-Cloud, Microsoft Fabric, AI Platforms, Information Technology, Star Schema, Data Management, Physical Data Models, Data Lakehouse, Cloud Migration, Stream Processing, Databricks - **Published:** October 27, 2026 - **Apply:** https://www.nettemps.com/us/en/WAF72FBC43CF9C54DD7.ntap ## About the Role As a technical leader, you will handle the entire data lifecycle, setting up automated data quality processes, master data management, data observability tools, and managing metadata to make sure all data is accurate, consistent, and easy to use for analytics and AI/LLM applications. Using secure CI/CD practices and containerization, the architect will translate requirements into practical solutions, provide implementation guidance, and drive data governance best practices. Strong skills in data modeling, SQL, cloud platforms (Azure or GCP), and APIs are required, with experience in large-scale data projects and exposure to the C3 AI platform will be highly preferred., * 8-12 years of overall experience in data architecture, enterprise data management, or platform architecture. * MS or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative field. * Proven experience designing and implementing large-scale data platforms and enterprise data solutions. * Experience leading architecture initiatives across multiple business functions and technology teams. * Strong background in cloud-based analytics and modern data platforms. Preferred Experience: * Hands-on experience with the C3 AI platform. * Experience working in an Embedded client environment, partner delivery model, enterprise SaaS implementation, or AI platform delivery role. * Experience delivering AI solutions for large enterprises or Fortune 500 clients. * Domain experience in manufacturing, energy, utilities, supply chain, aerospace, or other operationally complex industries. * Experience with demand forecasting, asset reliability planning, predictive maintenance, inventory optimization, or supply chain optimization. * Experience mentoring junior team members or leading small technical teams. ## Description We are seeking a Lead Data Architect with experience in data architecture, data modeling, and modern data platforms to design scalable, secure, and high-performing data solutions. In this role, you will orchestrate comprehensive system design, enforce resilient code architecture standards, and drive rigorous resource optimization across high-throughput infrastructure to maximize performance and minimize cloud compute costs. Beyond traditional data layouts, this position requires applying clean code practices, distributed software design patterns, caching mechanisms. Working closely with business and technical teams, you will oversee the design of robust semantic layers, conceptual, logical, and physical schemas, and optimized layouts for relational (SQL) and non-relational (NoSQL) configurations within modern data warehousing and data lakehouse systems., Enterprise Data Architecture * Define and maintain enterprise-wide data architecture standards, principles, and best practices. * Design scalable, resilient, and secure data architectures supporting analytics, AI/ML, LLM, and operational workloads. * Develop conceptual, logical, and physical data models that align with business objectives and enterprise architecture standards. * Architect modern data warehouse, data lakehouse, and data mesh solutions. * Drive data platform modernization initiatives and cloud migration strategies. Data Modeling & Semantic Layer Design * Design and optimize: Conceptual Data Models Logical Data Models Physical Data Models * Create enterprise semantic layers to support self-service analytics and business intelligence. * Establish standards for dimensional modeling, data vault, star schema, snowflake schema, and normalized data models. * Design scalable relational and non-relational data structures for diverse business use cases. * Ensure data models support reporting, advanced analytics, AI, and machine learning requirements. Modern Data Platform Architecture * Architect and govern data solutions on: Microsoft Fabric, Databricks, Snowflake, Azure Data Platform, and Google Cloud Platform (GCP) * Design data ingestion, transformation, storage, and consumption layers. * Establish best practices for batch, streaming, and Real Time data processing architectures. * Design architectures supporting hybrid and multi-cloud environments. Performance Optimization & Resource Efficiency * Drive optimization of compute, storage, and networking resources across cloud platforms. * Implement scalable data processing patterns for high-volume and high-throughput environments. * Design caching mechanisms and distributed processing strategies to improve platform performance. * Establish performance benchmarks, monitoring frameworks, and optimization standards. * Identify opportunities to reduce cloud infrastructure costs while maintaining performance and reliability. * Ensure efficient utilization of cloud resources through workload optimization and architecture reviews.