Senior Database Engineer

• Design, build, and support enterprise data solutions using Azure and Microsoft Fabric. 

• Create scalable Fabric Lakehouse, Fabric Warehouse, and hybrid warehouse architectures with raw, standardized, curated, and consumption-ready layers. 

• Design dimensional models, star schemas, facts, dimensions, data marts, semantic-ready datasets, and reusable data products. 

• Build production ETL/ELT using Fabric Data Factory, Azure Data Factory, SQL, Python, PySpark, notebooks, APIs, files, and event or batch integration patterns. 

• Engineer OneLake-aligned solutions, shortcuts, pipelines, notebooks, SQL endpoints, Power BI semantic models, and Direct Lake patterns when appropriate. 

• Create governed data foundations for generative AI, copilots, agents, search, and analytics using Microsoft Foundry or Azure OpenAI, Azure AI Search, and enterprise data sources. 

• Design and implement RAG workflows, including ingestion, chunking, metadata, embeddings, vector/hybrid retrieval, grounding, prompt design, citations, and evaluation. 

• Evaluate LLM solution quality, grounding, latency, cost, content safety, data leakage risk, and business fitness before production use. 

• Use tools such as Copilot in Microsoft Fabric, GitHub Copilot, Microsoft 365 Copilot, Copilot Studio, or approved enterprise copilots to accelerate development and build user-facing experiences. 

• Apply responsible AI practices, human review, access controls, privacy protections, prompt and model testing, auditability, and monitoring. 

• Implement data quality, lineage, observability, reconciliation, validation, security, and governance controls throughout the engineering lifecycle. 

• Use Git, pull requests, automated tests, CI/CD, environment promotion, and Infrastructure as Code for data pipelines, notebooks, database objects, and platform configuration. 

• Optimize workloads for performance, scalability, reliability, and cost across SQL, Spark, Fabric capacity, storage, pipelines, and semantic models. 

• Partner with BI, analytics, application engineering, DBAs, security, infrastructure, and business stakeholders on end-to-end solution architecture. 

• Provide technical leadership, code and design reviews, reusable templates, technical documentation, and mentoring. 

Required Qualification:

Minimum 7 years of professional data engineering, database engineering, data warehousing, or closely related experience, including senior-level design ownership.