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Enterprise Data Architect & AI Solutions Leader

AnswerRocket·US·Atlanta, Georgia, United States·senior
snowflakebigquerypower bitableau
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At AnswerRocket, we build transformative AI solutions that drive measurable results for Fortune 2000 Enterprises. For over a decade, we’ve helped industry leaders across sectors from consumer goods and construction to healthcare and financial services, harness AI to achieve tangible business outcomes. Our strength is the composition of our team: developers, data scientists, designers, architects, and AI/ML experts working alongside senior-level consultants. This combination allows us to solve enterprise AI challenges from strategy through implementation and optimization, and it is why some of the world’s largest companies seek us out. We're seeking an experienced Enterprise Data Architect Solutions Leader to join our growing team of AI and data professionals. In this pivotal role, you'll design and implement scalable, high-performance data architectures that power cutting-edge AI solutions while leading technical teams and driving enterprise transformation. Working at the intersection of enterprise data systems and generative AI technologies, you'll help us unlock the full potential of our data assets through modern lakehouse platforms and intelligent automation What You'll Do: Lead data strategy initiatives including current state assessments, enterprise architecture design, and governance frameworks Design and implement cloud-native data lakehouse platforms (Databricks, Snowflake, BigQuery) with medallion architectures Build real-time and batch data pipelines using modern ETL/ELT, streaming, and orchestration technologies Architect and develop generative AI solutions including RAG pipelines, multi-agent systems, and autonomous monitoring Create advanced analytics and BI solutions with modern self-service platforms (Tableau, Power BI) Lead technical teams, mentor data professionals, and drive innovation lab initiatives Conduct client discovery sessions and translate complex technical concepts for executive audiences Implement MLOps, feature stores, and AI/ML pipeli

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