Databricks Data & AI Analytics Architect

Dans le TOP10 des Sociétés de Conseil en Ingénierie en France, le Groupe SCALIAN intervient sur des activités de services en management de projets industriels, supply chain, architecture et développement de systèmes numériques embarqués, applicatifs de systèmes d’information et d’Intelligence artificielle dans des secteurs d’activité aussi variés que l’aéronautique, le spatial, l’automobile, le ferroviaire, les services, Le Luxe ou Le Retail, etc.

Créée en 1989, SCALIAN compte aujourd’hui plus de 5500 collaborateurs répartis dans 11 pays.

SCALIAN travaille pour des grands Groupes du CAC40 sur des projets en AT ou au forfait.

Labellisée Great Place to Work, SCALIAN connait une croissance de 20 % chaque année.

Pourquoi SCALIAN ?

• Parce que Scalian vous accompagne dans le développement de votre carrière : programme d’onboarding complet sur 1 an avec votre manager et votre RH, programmes de formation personnalisés, communautés techniques, événements internes
• Parce que Scalian favorise la Qualité de Vie au Travail : certifications Great Place to Work® et Best Workplaces for Women, prime de cooptation, prime vacances, accord télétravail
• Parce que Scalian développe une politique RSE concrète et ambitieuse : mobilité durable, actions environnementales, accord Handicap et mission handicap avec temps dédié.

Role Description:

We are seeking an experienced Data & AI Analytics Architect / Lead Engineer to modernize enterprise analytics platforms and drive adoption of AI-powered analytical solutions on Databricks. The role focuses on building scalable data ingestion frameworks, metadata-driven architectures, conversational analytic capabilities, and governed data products that improve business decision-making and reduce time to insight.

The organization operates multiple reporting and analytics solutions across Trading, Risk, Finance, and Operations using a mix of legacy data warehouse technologies and custom data pipelines.

Current challenges include:

· Fragmented ingestion and transformation patterns resulting in higher maintenance effort.

· Ongoing migration of analytical workloads from legacy platforms to Databricks.

· Increasing demand for self-service analytics, conversational data access, and AI-assisted decision support.

· Need for improved data quality, lineage, governance, and auditability.

· Requirement to accelerate insight generation and improve analytical scalability, reliability, and performance.

Skills:

· Strong expertise in Databricks, Spark, Delta Lake, Unity Catalog, SQL Warehouses, Databricks Workflows, Databricks Genie, and Genie One.

· Experience designing enterprise-scale data ingestion, ETL/ELT, metadata-driven, and watermark-based processing frameworks.

· Experience modernizing and migrating workloads from legacy data warehouses to Databricks.

· Strong SQL skills including query optimization, semantic modeling, and metadata-driven analytics.

· Experience building AI/LLM-powered analytics solutions, conversational interfaces, and agent-based architectures.

· Experience developing analytical assistants/copilots leveraging business metadata, governance rules, and semantic context.

· Ability to design conversational data exploration with drill-down analysis, context retention, and root-cause investigation.

· Experience with automated insight generation including KPI monitoring, trend analysis, anomaly detection, correlation analysis, and executive summaries.

· Good understanding of cloud data and analytics architectures covering ingestion, transformation, modeling, and serving layers.

· Knowledge of visualization and dashboarding concepts enabling business-friendly analytical experiences.

· Ability to work effectively across business and technology teams to improve data availability, reliability, and performance.

· Familiarity with Trading, Risk, Finance, Operations, or Supply Chain domains is highly desirable.