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AI Data Architect

AI Data Architect

Tata Consultancy Serviceshyderabad, India
7 days ago
Job description

Role : - AI Data Architect

Experience- 8 to 15years

Location - PAN India

Job 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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