Solutions Architect

FEQ427R74

At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer-focused team that values innovation and creativity, using your skills to create customised solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world!

The impact you will have:

• Act as a Solution Architect applying broad technical expertise across the data platform, including data science, machine learning, and business intelligence, while serving as the primary subject matter expert in data warehousing and data engineering.
• Lead the design and implementation of complex, end-to-end modern data architectures, with a deep focus on creating scalable and performant data warehouses and robust data ingestion pipelines.
• Form successful relationships with clients throughout your assigned territory, providing technical and business value to Databricks customers in collaboration with Account Executives.
• Scale best practices in data warehousing and engineering across your region by authoring reference architectures, how-tos, and demo applications.
• Operate as a trusted advisor, leading discussions on architecture, design, and implementation to ensure the successful adoption of the Databricks Data Intelligence Platform.

What we look for:

• Proven ability to operate as an expert generalist, capable of context-switching between different data disciplines and experienced in use case discovery, scoping, and delivering complex solution architecture designs to multiple audiences.
• Spike in Data Warehousing: hands-on experience with data modelling (e.g., dimensional modelling, 3NF), query optimisation, performance tuning, and migrating traditional data warehouses to modern lakehouse architectures.
• Spike in Data Engineering: Expert-level skills in designing, building, and optimising production-grade ETL/ELT pipelines using technologies like Spark.
• Prior experience with coding in a core programming language (i.e., Python, Java, Scala) and willingness to learn a base level of Spark.
• Proficient with big data Analytics technologies, including hands-on expertise with complex proofs-of-concept and public cloud platform(s).
• Engage customers in technical sales, challenge their questions, guide clear outcomes, and communicate technical and value propositions.
• Develop customer relationships and build internal partnerships with account executives and teams.