Job title: Pre-sales Solutions Architect (Databricks)

This newly created role will see you become a key player in Colibri Digital's Presales and solutioning team, owning the technical narrative for Databricks-centric opportunities across our pipeline. You will partner with Sales, Practice Leads, and Delivery to win Lakehouse, data engineering, ML, and GenAI deals on Databricks — from first technical conversation through to signed SOW.

You will work closely with prospective clients to understand their data estate, workloads, and business goals, then design tailored Databricks-based architectures and drive the technical sales motion: discovery, demos, POCs, RFP responses, and commercial shaping. The role demands strong Databricks platform fluency, broad cloud (AWS / Azure / GCP) literacy, commercial awareness, and the ability to make complex architectures land with both engineers and the C-suite.

Key Responsibilities

• Databricks solution advocacy: articulate the value of the Databricks Data Intelligence Platform — Lakehouse architecture, Delta Lake, Unity Catalog, Photon, Databricks SQL, Workflows, MLflow, Mosaic AI, and Databricks Apps — tailoring presentations and demos to each prospect's business and technical context.
• Technical consultation: act as the trusted Databricks expert during sales engagements, handling deep technical questions, addressing objections, and positioning Databricks against alternatives (Snowflake, Microsoft Fabric, native cloud data warehouses, open-source Spark / Iceberg stacks).
• Discovery and requirements gathering: lead structured discovery with data, analytics, and platform teams to capture current-state architecture, workloads, governance constraints, and target outcomes; translate findings into prioritised solution options.
• High Level Solution design: design Databricks-based reference architectures across AWS, Azure, and GCP, covering ingestion, Lakehouse modelling (Bronze / Silver / Gold), Unity Catalog governance, MLOps with MLflow, GenAI patterns (RAG, fine-tuning, agentic), and cost / performance optimisation.
• Demos and POCs: build and run compelling demos and time-boxed POCs on Databricks that prove value against agreed success criteria.
• RFPs and proposals: own the technical content of RFP / RFI responses, technical proposals, architecture diagrams, and Statements of Work in collaboration with the Commercial and Delivery teams; ensure SOWs are accurate, deliverable, and commercially sound.
• Cross-functional collaboration: act as the connective tissue between Sales, Practice Leads (Data Engineering, ML, GenAI, Platform), and Delivery, ensuring proposed solutions are deliverable, commercially sensible, and aligned to capacity and timelines.
• Partner alignment: work hand-in-glove with Databricks field teams — account executives, specialist SAs, partner managers — on joint pursuits, co-selling motions, and partner programmes.
• Delivery embedment: Periodically, you will be embedded with the delivery team in a billable role on client engagements — typically as a Databricks Solutions Architect during design or mobilisation phases — keeping you close to the platform and ensuring pre-sales commitments land cleanly in delivery.