AWS Snowflake Data Architect

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AWS Snowflake Data Architect based in India.** We are seeking an experienced Data Architect to design and evolve scalable, AI-ready data platforms that power advanced analytics, machine learning, and intelligent applications. This role will be responsible for creating the foundation behind enterprise AI initiatives, including conversational AI, RAG applications, predictive models, and autonomous agents. You will define modern data architectures, establish governance frameworks, and ensure secure, reliable access to critical business data. Working across cloud technologies, data engineering, and AI ecosystems, you will help shape solutions that drive innovation and operational impact. The position offers the opportunity to collaborate with global teams, influence architecture decisions, and contribute to next-generation technology platforms. You will play a key role in building resilient data systems designed for scale, performance, and future AI capabilities. ### Accountabilities: The role focuses on architecting, implementing, and continuously improving enterprise data platforms that support AI-driven products and business intelligence initiatives. Key responsibilities include: - Designing and implementing scalable data platforms using technologies such as Snowflake, Databricks, Delta Lake, and cloud-based solutions. - Building robust batch and real-time data pipelines using PySpark, Kafka, and Spark Structured Streaming. - Creating AI-ready data architectures that support analytics, machine learning, large language models, and retrieval-augmented generation applications. - Developing semantic models, metadata frameworks, data governance strategies, and data lineage solutions. - Designing and managing vector databases, embedding pipelines, and retrieval systems for AI applications. - Building and supporting ML/LLMOps workflows, including model deployment, monitoring, automation, and CI/CD processes. - Ensuring strong data security practices through access controls, governance standards, and compliance frameworks. - Establishing architecture best practices and mentoring engineering teams to improve technical capabilities. - Collaborating with technical and business stakeholders to translate requirements into scalable data solutions. ## Requirements: The ideal candidate brings extensive experience in data engineering, architecture, and modern cloud ecosystems, with strong technical expertise and communication abilities. Required qualifications include: - 12+ years of experience in Data Engineering or Data Architecture roles. - Strong hands-on experience with Snowflake, Databricks, PySpark, Kafka, Delta Lake, SQL, and Python. - Experience working with AWS services such as S3, Glue, Redshift, Bedrock, and Kinesis, or equivalent Azure technologies. - Practical knowledge of AI and data technologies including LangChain, LlamaIndex, OpenAI/Bedrock solutions, RAG architectures, and vector databases such as Pinecone, ChromaDB, FAISS, or OpenSearch. - Solid understanding of ML/LLMOps, data governance, data lineage, and CI/CD practices. - Experience designing secure, scalable, and highly available data platforms. - Strong problem-solving skills with the ability to manage complex technical challenges. - Excellent communication, collaboration, and stakeholder management skills. - Ability to work effectively in a global, remote-first environment. ## Benefits: - Remote-first work model with flexibility to work from locations where you perform best. - Opportunity to collaborate with international teams across multiple regions and industries. - Exposure to advanced AI, data engineering, and enterprise transformation projects. - Supportive environment focused on continuous learning, innovation, and professional growth. - Opportunities to work with diverse technologies and solve complex technical challenges. - Cult…