Data Architect - Leeds - Palantir

RP Recruitment Ltd
London
1 day ago
Create job alert

Data Architect

Location: UK (Hybrid)
Contract: Permanent or Contract
Seniority: Senior / Lead / Principal

Overview

My client is looking for a highly experienced Data Architect with deep expertise in Palantir Foundry to lead the design, modelling, and governance of next-generation data platforms. This role will shape how clinical, operational, and population-level insights are delivered using one of the most advanced data operating systems in the world.

Key Responsibilities

Lead the end-to-end architecture of Palantir, covering data integration, pipelines, transformations, ontology modelling, governance, and operational applications.
Own and evolve the enterprise ontology, defining object types, links, actions, and semantic relationships for clinical and operational domains.
Design scalable, modular, and governed data pipelines following Foundry best practices (transform patterns, DRY architecture, no circular dependencies).
Integrate structured, unstructured, streaming, and device/IoT datasets using Foundrys ingestion and connector frameworks.
Build ontology-driven data products, KPIs, data marts, and analytical frameworks for clinical pathways, care coordination, workforce planning, and command-centre operations.
Implement robust security, classification, and purpose-based access controls, ensuring full lineage, auditability, and regulatory compliance.
Work closely with clinicians, analysts, data engineers, DevOps teams, and senior leadership to guide platform adoption and architectural decision-making.
(AWS optional but advantageous) Support Foundry deployments on AWS including S3 data storage, KMS encryption, multi-AZ architecture, CloudWatch monitoring, and alignment to AWS Well-Architected Framework.

Required Qualifications & Experience

Extensive hands-on expertise in Palantir Foundry architecture, including pipelines, transforms, ontology, governance, and operational app development.
Strong understanding of healthcare datasets (EPR, PAS, FHIR/HL7, clinical coding, operational and workforce data).
Proven experience designing enterprise data models, semantic layers, or ontologies.
Strong background working within regulated environments such as NHS trusts, ICSs, central government, or large healthcare providers.
Excellent communication and stakeholder engagement skills, including the ability to influence technical and non-technical audiences.

Preferred Certifications (Highly Desirable)
Palantir Foundry Solution Architect Certification
AWS Solutions Architect

Associate/Professional
TOGAF / BCS Enterprise Architecture (optional)

Preferred Skills
Understanding of interoperability standards (FHIR, HL7v2, SNOMED CT).
Experience with cloud-native data engineering on AWS.
Knowledge of DevOps practices (CI/CD, IaC, GitOps).
Experience designing data quality frameworks and governance models

Please let me know if this mandate is of interest to you.

TPBN1_UKTJ

Related Jobs

View all jobs

Data Architect

Data Architect

Data Architect

Data Architect – Multi-Cloud – Eligible for Security Clearance

Data Architect - Halifax; Home Based

Data Architect

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.