24 Data Architect jobs in India available for remote work from home. Apply for positions such as Data Architect, Data Architect , Solutions Architect - Data Engineering and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Data Architect will lead multiple delivery pods across AI, Data Engineering, and Analytics projects while overseeing technical design and execution. They are responsible for managing cross-functional teams, ensuring project milestones are met, and maintaining high-quality delivery standards for clients.
The Data Architect will design and manage scalable, secure, and compliant data platforms using Snowflake within a medical device environment. They will also develop data models and pipelines while ensuring adherence to healthcare regulations and data standards.
Lead discovery sessions to translate complex client challenges into scalable, production-ready Data & AI architectures. Oversee the end-to-end delivery of enterprise solutions while mentoring engineering teams and advising executive stakeholders.
You will lead the end-to-end technical design and implementation of Salesforce Data 360 and Agentforce solutions to drive intelligent, AI-powered customer experiences. This involves architecting scalable data models, defining integration frameworks, and overseeing the project lifecycle from design through deployment.
The Solution Architect will design end-to-end data and analytics platforms while acting as a trusted technical advisor to clients. The role involves a balanced split between hands-on project delivery and presales activities such as solution scoping and proposal creation.
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Lead enterprise data and analytics architecture by designing scalable solutions and driving end-to-end data platform delivery. Mentor development teams, manage stakeholder relationships, and support technology strategy and pre-sales activities.
The Senior Data Architect leads the design and governance of enterprise data platforms, including lakehouse solutions and complex data models. This role collaborates with engineering and business teams to implement scalable, secure data products that support analytics and decision-making.
Design, develop, and manage enterprise-grade real-time data pipelines using Apache Kafka and the Confluent Platform. Collaborate with architects and stakeholders to implement scalable, fault-tolerant event-driven integration patterns.
Lead the design and delivery of scalable and secure data center infrastructure solutions from conception through deployment. Manage cross-functional teams, technical roadmaps, and vendor relationships to ensure project alignment with organizational objectives.
Lead the design and implementation of end-to-end production data solutions for global enterprise clients. Manage and mentor a team of Solution Architects and Data Engineers while collaborating with stakeholders to ensure successful project delivery.
Lead enterprise-scale data architecture initiatives and define cloud data strategies. Design scalable cloud-native platforms and drive data governance and analytics initiatives across business domains.
Architect and govern an enterprise AI data platform serving as the single source of truth for AI agents, RAG applications, and ML models. Design semantic layers, retrieval infrastructure, and LLMOps pipelines while ensuring strict data security and governance.
Lead the strategic design, architecture, and implementation of enterprise data solutions and business intelligence platforms for clients. Oversee cross-functional teams to develop data governance frameworks and ensure seamless data flow across cloud and on-premise systems.
![Smart Working Solutions is hiring for remote Big Data Architect (Remote, Full-Time) [IS002]](/assets/08150176-369d-44db-a4a7-778571334971.png){kind=small}
The Big Data Architect will define current and future-state data architectures, ensuring scalability and efficiency for data-driven products within the iGaming industry. This involves assessing the existing platform, performing gap analysis, and guiding technical decision-making across the software lifecycle.
The Data Platform Architect serves as the technical authority for the modern data ecosystem, responsible for designing high-performance, secure, and cost-effective data infrastructure. This role involves setting architectural standards, conducting design reviews, and bridging the gap between complex technical systems and business value.
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The Senior Architect will design and evolve enterprise integration architectures, focusing on API-first and event-driven patterns to ensure scalable system communication. They will lead modernization efforts for legacy systems and establish best practices for API governance, security, and distributed system reliability.
The role involves designing, building, and owning scalable data platforms on Google Cloud, taking an architectural role to drive end-to-end data solutions and define best practices. This includes delivering reliable, high-performance data pipelines and analytics platforms by collaborating with stakeholders, analysts, and data scientists.
Design enterprise data models, semantic architectures, and conversational AI solutions to enable trusted analytics and scalable data products. Lead architecture reviews and provide technical coaching to ensure solutions align with enterprise standards.
You will lead a delivery pod in designing and building modern data platforms on Microsoft Fabric and Azure for global clients. This role involves hands-on architecture, technical leadership, code reviews, and active participation in client-facing discovery and presales conversations.
The Director will lead the strategy, design, and governance of the enterprise data architecture while actively contributing to technical solutions. They will partner with engineering and business stakeholders to establish standards for data quality, modeling, and AI-ready data platforms.
The Data Architecture Lead will be responsible for shaping the enterprise data foundation by translating architecture standards into domain-aligned designs, defining consistent data structures, and partnering with engineering and analytics teams for implementation and adoption. This role enables trusted data products, analytics, operational reporting, and future AI use cases through modern data architecture practices.
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