Enterprise Data Architect

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.