Lead Data Engineer

Expert-level Python, Scala and PySpark: production-ready, modular, well-tested solutions; Spark workload troubleshooting; optimizing large-scale batch and streaming pipelines using Delta Lake.Strong SQL and data modelling (dimensional and normalised), schema design, data contracts.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), Azure Event Hubs.3+ years designing and shipping LLM-based systems in production: RAG pipelines, agentic / tool-calling workflows, chunking and embedding strategy, vector and hybrid retrieval, prompt engineering.Evaluation discipline: golden datasets, regression suites, accuracy and hallucination tracking, human-in-the-loop feedback.Hands-on with LangChain, LlamaIndex or LangGraph, plus at least one provider stack (Azure OpenAI, OpenAI, or Databricks Model Serving).Metadata-driven frameworks: schema inference, data profiling, lineage, catalogs.12-18 years of total experience in data engineering / data platform delivery.Proven enterprise-scale delivery of a medallion / lakehouse architecture.Azure security and governance: Entra ID, managed identities, RBAC, POSIX ACLs, Key Vault, private endpoints, PII handling.CI/CD and IaC: Azure DevOps, Terraform, Databricks Asset Bundles, automated testing of data pipelines.Clear technical writing and ability to present and defend designs to engineers and non-technical stakeholders.