AI Data Architect

Job description

**Job Title: AI Data Architect** **Experience Required:** 8 to 15 Years **Location**: Hyderabad/Bangalore **Role Overview:** 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. This role requires deep expertise in designs, develops, and deploys scalable and secure **data architectures** on cloud platforms to **support AI** **\& ML** initiatives. They bridge the gap between business needs and technical implementation by creating the necessary infrastructure for **data processing, model training** , and **inference** . This role requires expertise in cloud services, distributed computing, that handle **large** **datasets** and **complex** **workloads**for AI/ML frameworks, and MLOps to build robust systems **Key Responsibilities:** * **Architectural and Design:** 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. **Skills:** * **Cloud Platforms** : Deep knowledge and expertise in cloud data services and **ANY ONE** cloud platforms (AWS or Azure OR Google Cloud). * **Data and analytics** : Experience in **ANY ONE** of the following data platforms, Data modeling, and Distributed computing frameworks. 1. Databricks 2. Snowflake * **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. **Experience with ANY ONE of the following** **Cloud Native Data Services**: * **Azure**: Azure Data Factory, MS Fabric, Azure Databricks, Azure Synapse Analytics, Datalake Gen2, Stream Analytics and Azure Dedicated SQL Pool (ADW), * **AWS**: AWS Glue, AWS S3, AWS Athena, AWS Kinesis and AWS Redshift / EMR * **Google Cloud Platform (GCP)**: GCP Dataproc, GCP DataFlow, GCP BigQuery, GCP Cloud Storage, Cloud SQL and Pub Sub. * Other public cloud platforms such as Snowflake, Hadoop... **Qualifications:** * Bachelor's or Master's degree in Engineering or Technology. * 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.