Technical Manager – Data Architecture & AI (Databricks)

• 7+ years in the data field, of which at least 4 leading technical teams with direct responsibility for people and delivery.
• Demonstrable experience as a data solutions architect in enterprise environments (banking, industry, energy, telco, or public sector).
• Experience in consulting or professional services: client management, pre-sales, and working with technology partners.
• Proficiency in PySpark, SQL, and Python; orchestration (Airflow, Databricks Workflows) and CI/CD for data.
• Data governance: catalogs, quality, lineage, and data contracts.
• Cloud architectures in Azure and/or AWS
• Executive communication: ability to structure and defend architecture decisions before management committees.
• Structured thinking, results orientation, and autonomy in managing multiple simultaneous projects.

• Recent experience in generative AI and agentic architectures is highly valued.
• Databricks Certified Data Engineer Professional (or Associate with a demonstrable track record).
• Additionally valued: Azure Solutions Architect Expert, AWS Solutions Architect, or data governance certifications (DAMA/CDMP).

• Technical leadership role in a growing practice, with direct access to the innovation roadmap and the Databricks partnership ecosystem.
• Funded certification plan and dedicated time for training and innovation.
• Hybrid work model and a competitive compensation package according to experience.

We are looking for a Technical Manager who combines technical team leadership with deep expertise in Data & AI architecture on Databricks. You will act as the technical reference for the Data & AI practice, lead delivery teams in data platform projects, govern architecture decisions for strategic clients, and support technical pre-sales in Databricks ecosystem opportunities. You will report to the Data Platform Director.

• Lead multidisciplinary teams of data engineers and architects, including capacity planning, delivery monitoring, and performance management.
• Develop talent: technical mentoring, definition of career plans, and team certification on the Databricks platform.
• Manage the technical relationship with the client at a management level: steering committees, escalations, and expectation management.
• Define and validate end-to-end lakehouse architectures: ingestion, modeling (medallion), data governance, semantic layer, and analytical/AI activation.
• Design generative and agentic AI solutions on governed data (RAG, agents, MLOps/LLMOps), ensuring traceability, quality, and regulatory compliance.
• Establish technical standards, reusable frameworks, and accelerators for the practice.
• Act as the practice's leading Databricks expert: Unity Catalog, Delta Lake, Delta Live Tables / Lakeflow, Databricks SQL, Mosaic AI, governance, and platform FinOps.
• Lead migrations to Databricks from legacy platforms (SAS, Teradata, SAP BW, Hadoop) and greenfield projects on Azure/AWS.
• Collaborate with the Databricks partner ecosystem: technical support for pre-sales opportunities, PoCs, workshops, and RFP responses.
• Contribute to technical proposals and effort estimations in practice opportunities.
• Participate in internal innovation initiatives (proprietary frameworks, accelerators, company IP).