As a Senior Technical Architect / Engineering Manager specializing in AI & Data Platforms, your role will involve leading the design, development, and delivery of scalable AI-driven analytics platforms. You will be expected to leverage your deep expertise in data architecture, cloud technologies, and machine learning integration to manage cross-functional engineering teams effectively. **Key Responsibilities:**
**Architecture & Solution Design:**
Design end-to-end data architecture covering data ingestion, ETL pipelines, data modeling, data lakes / warehouses, BI, and analytics layers. - Develop scalable, secure, and high-performance systems on cloud platforms. - Architect multi-tenant and modular solutions for enterprise-grade applications. - Drive system design decisions, performance optimization, and scalability planning. - **AI & Advanced Analytics:**
Integrate AI/ML capabilities such as LLM-based solutions, predictive analytics, anomaly detection models, and natural language analytics. - Collaborate with data science teams to deploy and scale ML models. - **Data Engineering & Platform Development:**
Build and optimize ETL pipelines using modern data tools. - Design robust data models and transformation frameworks. - Ensure data quality, governance, and validation processes with large-scale datasets. - **Engineering Leadership:**
Lead and mentor cross-functional engineering teams (Data, BI, AI). - Drive sprint planning, task allocation, and delivery execution. - Establish coding standards, code reviews, and engineering best practices for timely delivery of high-quality solutions. - **Integration & Security:**
Design API-driven architectures and system integrations. - Implement secure authentication mechanisms like JWT, OAuth, etc. - Ensure compliance with enterprise security and data protection standards. - **Stakeholder Management:**
Collaborate with business stakeholders to understand requirements and provide strategic input for data-driven decision-making. **Required Skills & Qualifications:**
**Technical Skills:**
Strong expertise in system architecture, data engineering, cloud platforms (Azure / AWS / GCP). - Hands-on experience with Azure Data Factory, Data lakes, ETL pipelines, Python, SQL, API design, and performance optimization. - Proficiency in AI & Machine Learning, Analytics & Visualization, and Leadership & Soft Skills. **Preferred Qualifications:**
Experience in multi-tenant SaaS platform architecture, DevOps practices, and domain experience in Finance, HR, Sales / Marketing Analytics, Supply Chain / Logistics. - Bachelors degree in engineering / technology; Masters degree (MBA / Analytics / Data Science) preferred. If you are interested in this challenging opportunity, kindly send your updated resume for consideration. As a Senior Technical Architect / Engineering Manager specializing in AI & Data Platforms, your role will involve leading the design, development, and delivery of scalable AI-driven analytics platforms. You will be expected to leverage your deep expertise in data architecture, cloud technologies, and machine learning integration to manage cross-functional engineering teams effectively. **Key Responsibilities:**
**Architecture & Solution Design:**
Design end-to-end data architecture covering data ingestion, ETL pipelines, data modeling, data lakes / warehouses, BI, and analytics layers. - Develop scalable, secure, and high-performance systems on cloud platforms. - Architect multi-tenant and modular solutions for enterprise-grade applications. - Drive system design decisions, performance optimization, and scalability planning. - **AI & Advanced Analytics:**
Integrate AI/ML capabilities such as LLM-based solutions, predictive analytics, anomaly detection models, and natural language analytics. - Collaborate with data science teams to deploy and scale ML models. - **Data Engineering & Platform Development:**
Build and optimize ETL pipelines using modern data tools. - Design robust data models and transformation frameworks. - Ensure data quality, governance, and validation processes with large-scale datasets. - **Engineering Leadership:**
Lead and mentor cross-functional engineering teams (Data, BI, AI). - Drive sprint planning, task allocation, and delivery execution. - Establish coding standards, code reviews, and engineering best practices for timely delivery of high-quality solutions. - **Integration & Security:**
Design API-driven architectures and system integrations. - Implement secure authentication mechanisms like JWT, OAuth, etc. - Ensure compliance with enterprise security and data protection standards. - **Stakeholder Management:**
Collaborate with business stakeholders to understand requirements and provide strategic input for data-driven decision-making. **Required Skills & Qualifications:**