AI Data Architect

3 weeks ago

Bangalore Urban Karnataka India, IN Tata Consultancy Services Full time

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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