Programming & Data Engineering
The experience expected from applicants, as well as additional skills and qualifications needed for this job are listed below.
Expert - level proficiency in Python, Scala, and PySpark, with a strong track record of designing and delivering production-ready, modular, and well-tested solutions; developing and troubleshooting Spark workloads; and optimizing large-scale batch and streaming data pipelines using Delta Lake and Spark technologies.
Strong SQL and data modelling — dimensional and normalised; schema design and data contract definition.
Databricks expertise — Delta Lake, Unity Catalog, Jobs & Workflows, cluster and pool management, performance tuning, Model Serving.
Azure data stack — ADLS Gen2 (zone design, ACLs, lifecycle), Azure Data Factory (parameterized / metadata-driven frameworks, error handling), Azure Event Hubs.
AI & Machine Learning
3+ years designing and shipping LLM-based systems in production: RAG pipelines, agentic / tool-calling workflows, structured output, chunking and embedding strategy, vector and hybrid retrieval, and prompt engineering.
Evaluation discipline — golden datasets, regression suites, accuracy and hallucination tracking, human-in-the-loop feedback loops; you measure AI quality, not assert it.
Hands-on experience with LangChain, LlamaIndex, or LangGraph, plus at least one provider stack (Azure OpenAI, OpenAI, or Databricks Model Serving). xhqgsiq
Metadata-driven thinking — schema inference, data profiling, lineage, catalogs, and configuration-driven frameworks that onboard the next source without new code.
Lead Data Engineer in cary at Unknown Company
This position is listed as contract and hybrid.