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.

Hands-on ownership, sound judgment, attention to detail, and disciplined follow-through.

Clear written and verbal communication with technical and non-technical stakeholders.

Ability to mentor team members, lead design or incident reviews, and document repeatable standards.

Commitment to security, data privacy, responsible technology use, and continuous learning.

Here at Havas across the group we pride ourselves on being committed to offering equal opportunities to all potential employees and have zero tolerance for discrimination. We are an equal opportunity employer and welcome applicants irrespective of age, sex, race, ethnicity, disability and other factors that have no bearing on an individual’s ability to perform their job.