The Palantir Solution Architect is responsible for guiding multi-skilled agile teams in the design and delivery of modern, enterprise-grade data solutions. This role calls for a quality-driven pragmatist who can balance trade-offs to deliver complex outcomes successfully. As a recognised authority in data technology, the architect provides strong technical leadership, strategic insight, and thought leadership across projects and teams.

Key Responsibilities

• Leading the successful implementation of both functional and non-functional solution designs.
• Collaborating with Operations and Infrastructure architects to build and productionise robust, resilient, and maintainable data solutions.
• Working closely with customer architects to agree technical designs, offering challenge, guidance, and expert advice to support sound decision-making.
• Shaping policy, standards, and best practice while sharing knowledge and mentoring colleagues across the wider team.
• Managing and estimating delivery timelines, ensuring solutions are aligned with wider project goals.
• Owning the technical solution design during pre-sales activities and supporting bid and proposal development.
• Contributing significantly to the data community and broader organisational data capability.
• Managing, coaching, and developing team members, focusing on performance, career growth, and providing direction during problem-solving activities.

Essential Requirements

• Proven experience leading multiple teams as a data solution architect, with ownership of complex, interconnected systems.
• Expertise in designing, building, and productionising modern data-intensive applications, including orchestration and operationalisation.
• Broad understanding of the full data technology ecosystem—covering ingestion, transformation, storage, presentation, and consumption—and the ability to integrate these effectively.
• Strong strategic design thinking, including conceptualising problems, defining approaches and roadmaps, realising architectures, and managing risks.
• Solid understanding of both traditional and contemporary data warehousing approaches.
• Experience deploying data-processing platforms from major vendors such as AWS, Azure, GCP, or Databricks.
• Proficiency in one or more of Java, Scala or Python, with the ability to contribute hands-on when required.
• A demonstrable commitment to developing people through coaching, mentoring, and team leadership.

Desirable Skills and Experience

• Knowledge of broader Data Architecture concepts, including Master Data Management, data masking, governance, provenance, and lineage.
• Experience in technical evaluation and product selection.
• Familiarity with data integration techniques such as messaging, queuing, change data capture, or data virtualisation.