Data Platform Architect – Data & AI Practice
New
J
JobgetherData and AI
Remote working arrangement based in IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least five years of direct experience working with North American customers.
- Required Skills
- AWSGCPSnowflakeAzureDatabricks
Requirements
- Extensive experience designing and implementing enterprise data platforms.
- Strong hands-on architecture, solution engineering, and technical leadership background.
- Proven experience architecting enterprise data solutions on AWS.
- Solid understanding of Azure and GCP architectures, capabilities, roadmaps, and comparative trade-offs.
- Deep expertise in Databricks and Snowflake, including lakehouse architecture, data engineering, pipelines, integration patterns, and native AI capabilities.
- Working knowledge of RAG, LLM integration, agentic AI workflows, and MCP-based connectivity.
- Strong understanding of master data management, data quality, governance, security, and production operations.
- Familiarity with Reltio, Informatica, Collibra, and Alation.
- At least five years of direct experience working with North American customers.
- Experience with technical discovery, architecture workshops, solution advisory, stakeholder management, and client-facing technical discussions.
- Ability to translate business requirements into technical designs, build working prototypes, evaluate alternatives, and guide implementation.
- Preferred experience with enterprise modernization, AI-ready data platform implementations, technology partnerships, consulting engagements, or technical practice development.
Responsibilities
- Design and implement scalable, cloud-native enterprise data platforms covering ingestion, integration, processing, analytics, governance, and AI enablement.
- Develop data solutions primarily on AWS and evaluate Azure and Google Cloud Platform capabilities where appropriate.
- Design data integration patterns and platform capabilities for RAG, LLM integration, agentic workflows, and MCP-based connectivity.
- Architect Databricks and Snowflake solutions, including lakehouse environments, data engineering pipelines, and integration frameworks.
- Lead technical discovery sessions, architecture workshops, proof-of-concepts, and minimum viable product development.
- Develop strategies to migrate and integrate legacy enterprise data systems into modern cloud platforms.
- Define approaches to data governance, quality, security, production operations, and enterprise data management platform integration.
- Advise North American customers, facilitate architecture discussions, and communicate recommendations to business stakeholders and technical teams.
- Guide engineering teams through implementation and help resolve complex technical challenges.
- Develop reference architectures, reusable accelerators, implementation patterns, and technical frameworks.
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