AI Data Architect

4 weeks ago

New Delhi, India Tata Consultancy Services Full time

Role:- AI Data Architect Experience- 8 to 15years Location - PAN IndiaJob Description We are seeking an inventive Data Architect for AI with 8–15 years of experience to lead the strategic design and implementation of enterprise-scale AI solutions. 8+ years of experience in ETL/ELT, Big Data cloud data solutioning, with at least 3 years in architectural leadership roles. • Proven track record of delivering enterprise Data solutions on a scale. • Strong understanding of Data models and Data pipelines and cloud-native data architectures. • Excellent communication, stakeholder management, and leadership skills. Create and document scalable, secure, and cost-effective data architecture in the cloud (AWS/Azure/GCP) to support AI/ML data workloads. • Solution development: Build, optimize, and deploy end-to-end data solutions, such as recommendation data processing engines and data analytic engines. • Data Engineering: Proficiency in Data pipelines, ETL processes, Big Data Analytics and data management (SQL, NoSQL, data cleaning). • Technical implementation: Select and implement appropriate technologies, including data lakes, batch processing, real-time processing systems and MLOps tools. • Collaboration: Work with stakeholders, data scientists, and other teams to translate business requirements into technical specifications and ensure successful technical delivery. • System management: Ensure the reliability, performance, and security of Data & AI intensive systems. Must-Have Skills: • Cloud Platforms: Deep knowledge and expertise in cloud data services and platforms (AWS, Azure, and Google Cloud). • Data and analytics: Experience in Big data platforms, Data modeling, and Distributed computing frameworks like Databricks, Snowflake, Hadoop or Spark. • AI/ML knowledge: Experience in machine learning frameworks, platforms, and MLOps (Machine Learning Operations) practices. • Programming and scripting: Proficiency in languages like Python, Spark and SQL for data manipulation and system development. • Technical communication: Strong ability to document architectures and communicate complex technical concepts to both technical and non-technical audiences.

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