Our client is looking for a Senior Enterprise Technical Architect -Data in the Dallas, TX area. This is a full-time position and not open to contract or C2C candidates. All applicants must be eligible to work in the US without sponsorship. Key Responsibilities: Develop and Drive Data Strategy: Formulate a comprehensive data strategy and technology vision to support various service lines and technical disciplines. Use a holistic approach to conduct enterprise analysis, design, planning, and implementation, ensuring alignment with business goals. Document and Communicate Architecture: Create architectural models and views to illustrate how the organization's current and future data needs will be met in an efficient, sustainable, and flexible manner. Serve as Data Strategy Lead: Act as the primary liaison between Digital & Technology (D&T) and the business on all matters related to data architecture and strategy, leading as the cloud data architect for transformation programs. Data Architecture Leadership: Leverage extensive experience in data architecture to execute large-scale data platform modernization or migration projects from inception through production. Enterprise Data Integration: Bring a strong background in data warehouse technologies, data pipelines, and cloud platforms to manage and integrate enterprise data effectively. Collaborate with Stakeholders: Partner with technical teams, business units, and end-users to design modern data applications and platforms, selecting appropriate technologies based on business strategy and technical requirements. Ensure Architectural Compatibility: Provide data architecture expertise during system development, ensuring compatibility with existing and future enterprise data architecture. Develop AI & Analytics Strategies: Collaborate to create roadmaps for AI, machine learning, and advanced analytics, including technologies like natural language processing, neural networks, computer vision, data lakes, and ML platforms. Transition to Modern Data Platforms: Develop and review execution plans with system owners to move from legacy systems to modern data-centric platforms. Drive consensus to execute solutions. Envision Future State Architectures: Define the future state of data platforms using architectural artifacts and validate proposed architectures through proofs-of-concept or MVPs. Analyze and Document Systems: Lead the analysis of current application and integration landscapes and create future-state architectures and roadmaps. Provide Technical Leadership: Offer guidance on designing scalable data marts, data lakes, and data warehouses, addressing complex technical issues and supporting engineering teams. Qualifications: Education: Bachelor's degree in a STEM field (Science, Technology, Engineering, Mathematics). Cloud Expertise: In-depth knowledge of cloud platforms, particularly AWS and Azure. Technical Proficiency: 4+ years of experience developing enterprise data strategies. 8+ years in solution architecture with a focus on data technologies. 5+ years working with AWS/Azure data, analytics, and AI services. Expertise in data platforms and integration tools such as Snowflake, Snaplogic, Collibra, Informatica, etc. Proficiency with BI analytics tools like Tableau and Power BI. Experience in AI/ML, including Generative AI and Large Language Models (LLMs). Strong ETL pipeline implementation experience. Data modeling expertise, including data warehouses, data lakes, and data marts. Technical and Commercial Insight: Solid understanding of creating technology solutions and delivering outcomes that align with business needs. Skills and Attributes: Effective Communication: Strong written, verbal, and presentation skills, able to convey complex technical concepts to both technical and non-technical audiences. Learning Agility: Interest in and ability to adopt emerging technologies (e.g., knowledge graphs, data fabric, generative AI) to address business challenges. Innovation Mindset: Proactive in experimenting with new technologies and staying updated with the latest developments in AI/ML, data engineering, and cloud-native solutions. Design Focus: Skilled in designing with consideration for timeliness, cost, and quality, with the ability to identify and mitigate risks. Digital Transformation Driver: Experience with transformation initiatives, target operating models, cost optimization, and performance improvements. Customer-Centric: Strong focus on user experience and dedication to understanding customer needs. Agile Methodology Knowledge: Good understanding of agile development processes to align with engineering teams. This role is ideal for a self-motivated, innovative leader with a passion for modernizing data platforms and driving digital transformation across the organization.