Senior Database Engineer

Agency :

Havas Creative

Job Description :

The Senior Database Engineer is a hands-on senior engineering role responsible for designing, building, optimizing, and evolving modern Microsoft data platforms across Azure and Microsoft Fabric. The position owns cloud data engineering, enterprise warehouse and lakehouse architecture, data integration, semantic consumption, and AI-ready data products. The successful candidate brings a minimum of seven years of data engineering, database engineering, or data warehousing experience, including practical experience enabling generative AI solutions with copilots, large language models, retrieval-augmented generation, embeddings, vector or hybrid retrieval, prompt engineering, model evaluation, and responsible AI controls.

• 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.