Senior Solutions Architect
The Senior Solutions Architect will design and demonstrate end-to-end data and AI solutions, guide enterprise customers through technical pre-sales engagements, and deliver complex proofs of concept. The role requires strong data science, generative AI, programming, cloud, and customer-facing expertise, plus coaching experience.
About the job
Responsibilities
- Develop customer engagement strategies with Account Executives for the designated territory.
- Coach junior Solutions Architects and teams on use-case prioritization and building technical champions.
- Influence stakeholders through complex engagements involving the broader cloud ecosystem and third-party applications.
- Act as an expert solutions architect and trusted advisor for data analytics architecture, design, and adoption of the Databricks Lakehouse Platform.
- Develop customer-facing collateral and lead workshops, seminars, and meetups.
- Pursue development in technical specialization, industry vertical thought leadership, strategic customer vision, or people management.
Requirements
Technical Qualifications
- Hands-on experience in technical pre-sales or consultancy, with a strong background in data science, traditional machine learning, deep learning, artificial intelligence, or generative AI.
- Ability to architect end-to-end Data and AI solutions, including generative AI concepts such as fine-tuning, retrieval-augmented generation (RAG), and MLOps for LLMs.
- Experience with open-source or ISV tools such as Dataiku, Domino, or DataRobot.
- Strong proficiency in a core programming language such as Python or SQL, with willingness to learn or existing knowledge of Spark.
- Proficiency with big data analytics technologies and public cloud platforms such as AWS, Azure, or Google Cloud.
- Hands-on expertise designing and delivering complex proofs of concept.
Pre-Sales and Customer-Facing Skills
- Ability to engage customers in a technical sales capacity, challenge assumptions, guide discussions toward clear outcomes, and communicate technical and business value.
- Experience across the full pre-sales lifecycle, including use-case discovery, solution scoping, and complex solution architecture design for technical and executive audiences.
- Customer-centric approach with a passion for building client relationships and internal partnerships with account teams.
Leadership
- Experience coaching and mentoring junior team members in technical and customer-facing skills.
Logistics
- Ability to commute regularly to the London office.
- Willingness and ability to travel approximately 20–30% across the UK&I and EMEA for customer visits.
Nice to Have
- Databricks or other relevant cloud and data certifications.
Compensation and Benefits
- Comprehensive benefits and perks are offered, with regional details available through Databricks.
Skills
Python, SQL, Spark, AWS, Microsoft Azure, GCP, Big Data Analytics, Generative AI, Machine Learning, Deep Learning, RAG, MLOps, LLMs, Databricks, Dataiku
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