Lead Data Engineer

Programming & Data Engineering

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).

Metadata-driven thinking — schema inference, data profiling, lineage, catalogs, and configuration-driven frameworks that onboard the next source without new code.