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Product Specialist - Azure Lakehouse

Databricks
London
8 months ago
Applications closed

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At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. Our customers leverage the Databricks Data Intelligence Platform to power their mission critical Data and AI applications to improve how their organisations leverage data and insights to make better decisions, faster. Customers rely on Databricks for the full range of data workloads, including data engineering, ETL, near real-time streaming, machine learning, SQL analytics, and advanced analytics. 

As a Product Specialist - Azure Lakehouse (Sr. Specialist Solutions Architect) you will be a deep technical expert in Data Warehousing and in how customers can be successful with these use-cases in the Lakehouse paradigm. You will work closely with both Product Management and the EMEA Field Engineering and Sales teams to act as the technical bridge between these critical organisations to help make the Data Intelligence Platform vision a reality for our customers. You will provide thought leadership on best practices around how to build a Lakehouse in Azure in particular and how Databricks integrates with the wider Azure ecosystem. You will work closely with the Databricks Product Management team to drive adoption of Azure Lakehouse features and ensure a consistent product vision for the EMEA technical field. You will work closely with Sales and FE leaders to help drive adoption of Azure Lakehouse by identifying target accounts and messaging. You will support our field teams in competing with existing data warehouses. You will support enablement activities for the EMEA technical field and sales team and drive customer success through direct engagement and scale your expertise across EMEA.

You will report directly to the Sr. Director Product Specialists Databricks Field Engineering and will be located in London. Databricks Field Engineering works with our current and future customers to grow adoption, win technical validations and advise customers on Azure Lakehouse best practices. The Product Specialist - Azure Lakehouse owns the enablement and escalations within the EMEA Field Engineering team around relevant features.

The impact you will have:

Deliver thought leadership in Azure Lakehouse best practices for the Databricks Data Intelligence Platform in the form of blogs, webinars, how to guides and technical know-how to the EMEA technical community and beyond. Working with sales and FE leaders drive adoption of Azure Lakehouse across EMEA Provide a strong, informed, and data-driven perspective in conversations with the Product and Engineering teams to influence our product strategy and priorities in how customers can and should bring Databricks into their Data strategies. Provide guidance and oversight for large-scale enterprise Azure Lakehouse competitive scenarios, serving as a trusted technical advisor to senior tech leads and executives Act as the level three point of escalation on the toughest technical challenges in the field that customers face to drive customer success. Provide key messaging and approaches to ensure the EMEA technical field is prepared for competitive conversations

What we look for:

Experience in designing and delivering cloud-based Data Warehousing Solutions in a client or customer environment Ability to advise customers in Data Warehousing architecture: Prepare Databricks stakeholders for internal conversations and communicate directly, including anticipating blockers and address them before they become an issue Cross-Cloud Expertise: Help customers build a multi-cloud analytics ecosystem with Databricks at the centre and provide solutions for customers looking for disaster recovery, fault tolerance and backup Certification and/or demonstrated competence in the Azure ecosystem Demonstrated competence in the Lakehouse architecture including hands-on experience with Apache Spark, Python and SQL Excellent communication skills; both written and verbal Experience in pre-sales selling highly desired
National AI Awards 2025

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