The Role
Own Databricks-centric presales: lead discovery, design Lakehouse reference architectures, run demos/POCs, produce RFPs/SOWs, and align Sales, Delivery, and Databricks partner teams to win data engineering, MLOps, and GenAI deals.
Summary Generated by Built In
This newly created role will see you become a key player in our 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.
Skills, Knowledge and Expertise
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or related field.
- Proven experience in technical pre-sales, solutions architecture, or hands-on consulting on the Databricks platform (or a comparable Lakehouse / big data stack).
- Strong working knowledge of the Databricks Data Intelligence Platform: Lakehouse architecture, Delta Lake, Apache Spark, Unity Catalog, Databricks SQL, Workflows, MLflow, Mosaic AI / model serving, and at least one cloud deployment (AWS, Azure, or GCP).
- Confident designing and presenting Lakehouse and data platform architectures, including ingestion patterns, medallion modelling, governance, MLOps, and GenAI workloads (RAG, fine-tuning, agentic patterns).
- Demonstrable track record running discovery, demos, POCs, and RFP responses for complex data / AI deals, and communicating with audiences ranging from engineers to C-level executives.
- Strong commercial awareness — comfortable shaping SOWs, T-shirt-size estimates, and linking technical choices to business value, TCO, and time-to-value.
- Exceptional communication, presentation, and negotiation skills.
- Databricks certifications (e.g. Data Engineer Associate / Professional, Machine Learning Associate / Professional, Databricks Certified Solutions Architect) and complementary AWS / Azure / GCP certifications are highly desirable.
- Willingness to travel within the UK (and occasionally further) as required to meet business needs.
Benefits
- Remote Working: Flexible options to support your best work.
- Be at the forefront of technological innovation, working with a talented team passionate about making a difference.
- Opportunity to Work on Cutting-Edge Projects: Engage with innovative technologies and make a significant impact in the field.
- A Collaborative, Inclusive, and Dynamic Work Environment: Be part of a culture that values diversity, collaboration, and continuous improvement.
- Top tech including a New MacBook Pro.
About
We are passionate about helping businesses navigate the rapidly changing and complex world of emerging technologies. We create well-structured, secure, scalable solutions at speed to provide the foundation for groundbreaking change.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or related field.
- Proven experience in technical pre-sales, solutions architecture, or hands-on consulting on Databricks or comparable Lakehouse stack.
- Strong working knowledge of Databricks Data Intelligence Platform (Delta Lake, Apache Spark, Unity Catalog, Databricks SQL, Workflows, MLflow, Mosaic AI).
- Experience with at least one cloud deployment: AWS, Azure, or GCP.
- Ability to design and present Lakehouse architectures, ingestion patterns, medallion modelling, governance, MLOps, and GenAI workloads.
- Demonstrable track record running discovery, demos, time-boxed POCs, and responding to RFPs for complex data/AI deals.
- Strong commercial awareness: shaping SOWs, estimates, linking technical choices to TCO and business value.
- Exceptional communication, presentation, and negotiation skills.
- Databricks and/or complementary AWS/Azure/GCP certifications (Data Engineer, ML, Solutions Architect)
- Willingness to travel within the UK and occasionally further as required.
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The Company
What We Do
At Nasstar, we specialise in transformative technology. Our integrated suite of managed services delivers everything from cloud optimisation and application modernisation to networking, security and self-serve tools. With a consultative approach at our core, we modernise and manage technology to help our clients succeed in today's competitive business world. Through strategic consultation, to implementation and management, we provide the vision and the mechanics needed to create transformational change for our clients.
