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Remote role plus broad skillset increases applicant density despite seniority filtering.
Role requires deep data architecture and platform expertise, so cross-industry transferability is limited.
Very specific 12+ years requirement and many mandatory technologies make filters strict.
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Design and implement scalable data platforms using Snowflake, Databricks, Delta Lake, and cloud technologies (AWS or Azure).
Build batch and real-time data pipelines with PySpark, Kafka, Spark Structured Streaming supporting AI/ML, LLMs, and RAG applications.
Develop and manage AI-ready data architectures including semantic models, vector databases, ML/LLMOps pipelines, data governance, and ensure platform security and compliance.
12+ years of experience in Data Engineering or Data Architecture required.
Strong technical skills with Snowflake, Databricks, PySpark, Kafka, Delta Lake, SQL, Python, and AWS (S3, Glue, Redshift, Bedrock, Kinesis) or Azure.
Hands-on experience with AI-related tools such as LangChain, LlamaIndex, OpenAI/Bedrock, RAG, Vector Databases (Pinecone, ChromaDB, FAISS, OpenSearch).
Work Experience Required: 12+ years; Immediate joining preferred.
Experienced architect capable of leading enterprise-scale data platform design integrating advanced AI/ML and LLM capabilities.
Strong operational focus on building compliant, secure, and governed data architectures with end-to-end AI pipeline expertise.
Demonstrated ability to mentor teams and define architecture best practices in data engineering within cloud environments.