Forward Deployed Engineering - Senior Architect
About this role
Complex data and AI challenges often prevent organizations from extracting maximum value from the Databricks platform, creating a need for experts who can bridge technical execution with customer success. Databricks requires a Forward Deployed Engineering Senior Architect in London to own system architecture, guide design decisions, and deliver production-grade solutions for enterprise clients.
Daily responsibilities involve embedding directly with customer teams, scoping technical delivery work, and building end-to-end applications that span data engineering, machine learning, and user interfaces. Ideal candidates combine deep distributed computing knowledge with exceptional customer empathy, adapting quickly to new technologies while managing technical scopes and stakeholder relationships across complex environments.
What you will do
- Lead impactful customer technical projects by delivering production-grade systems, reference architectures, custom applications, and data ingestion and ML model integration.
- Guide strategic customers through transformational big data projects including end-to-end design, build, and deployment.
- Work with engagement managers to scope technical delivery work with input from the customer.
- Guide customers on architecture and design to ensure successful understanding, evaluation, and adoption of Databricks.
- Collaborate with internal engineering and support teams to provide product feedback and guide rapid resolution for engagement issues.
- Embed with customer teams, engaging with stakeholders from technical individual contributors to executives.
- Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the product roadmap.
What you need
- Bring strong years of experience in data engineering, data platforms, analytics, or software engineering.
- Feel comfortable writing code in Python, Scala, JavaScript, TypeScript, and modern frameworks.
- Possess working knowledge of two or more common cloud ecosystems such as AWS, Azure, and GCP, with expertise in at least one.
- Demonstrate deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals.
- Show familiarity with continuous integration and continuous deployment pipelines for production environments.
- Have working knowledge of MLOps, machine learning models, and AI APIs.
- Design and deploy performant production end-to-end data architectures combining pipelines, models, and user interfaces.
Nice to have
- Databricks Certification preferred but not essential
Skills and tech stack
Questions candidates ask
Will travel be required for this position?
Travel to customers is required 20% of the time. This ensures you can effectively embed with client teams and drive projects forward.
What kind of technical background is needed for this role?
Candidates need experience in software engineering, data platforms, or data engineering with coding fluency in Python, Scala, JavaScript, or TypeScript. Familiarity with distributed computing in Apache Spark and cloud ecosystems like AWS, Azure, or GCP is also required.
Who will I work with across the organization?
You will collaborate cross-functionally with engineering, product, and developer relations teams. Additionally, you will work closely with engagement managers, project managers, and customer stakeholders ranging from technical individual contributors to executives.