Senior Palantir MDM Engineer

We are currently seeking a Senior Palantir MDM Engineer who will be responsible for the design and delivery of enterprise-grade financial data, analytics and AI capabilities using Palantir Foundry. The role owns the end-to-end journey of Finance data, from source-system understanding and ingestion through transformation, business-rule implementation, data modelling, governance, Ontology and data-product development, to dashboards, automated reports, AI-powered insights and conversational analytics.The engineer will partner with Finance, Data & AI, source-system teams, data owners and business SMEs to translate financial reporting and analytical requirements into governed, reusable, secure and scalable data products. The ideal candidate combines deep Palantir engineering capability with Finance analytics, Ontology design, governance/MDM and applied AI. This is not a conventional pipeline-only developer role; the successful candidate must be capable of owning the technical design and delivering governed, business-ready outcomes.Our client based in Dubai, is one of the largest and most luxurious hospitality brands in the region. This position is a contract role with an initial duration of 12 months and is renewable.

Key Responsibilities

Design, build and maintain ingestion pipelines integrating financial and operational data from enterprise source systems and data lake platforms into Palantir Foundry.Develop scalable ingestion patterns for structured and semi-structured data, including incremental processing, historical loads, reconciliation and error handling.Build, deploy and support Palantir Foundry pipelines, transformations and curated datasets.Work with source-system SMEs to document structures, interfaces, dependencies, refresh cycles and authoritative sources.Optimize pipelines for reliability, performance, maintainability, observability and operational support.Translate Finance requirements, hierarchies, mappings, accounting logic and reporting rules into scalable transformation logic and reusable data models.Implement governed measures and business rules for Actual, Budget, Forecast, Prior Year, P&L, Revenue, Expenses, EBITDA, cost centres, departments, properties/SBUs and Group reporting.Develop certified Finance datasets for reporting, analytics, AI and downstream applications.Implement reconciliation controls between approved source systems and Foundry datasets.Support historical snapshots, trend analysis, point-in-time reporting and cross-domain analysis with relevant operational KPIs.Design and implement Palantir Ontology representing Finance and related enterprise business concepts.Define business objects, properties, relationships, actions and hierarchies and map physical datasets to reusable business objects.Model relationships across financial and operational domains and maintain consistency with agreed definitions, master data and governance standards.Build the semantic and contextual layer required for analytics, workflows and AI solutions.Establish end-to-end lineage from source systems through ingestion, transformations, business rules, datasets, Ontology and consumption.Implement automated data-quality controls for completeness, validity, accuracy, consistency, uniqueness, referential integrity and freshness.Define quality thresholds, exception handling, monitoring, reconciliation and issue-management processes with business data owners.Implement metadata classification, business and technical metadata, sensitivity tagging and critical-data-element tagging.Document business owners, technical owners, data stewards, authoritative sources and data classifications.Ensure analytical and AI outputs are traceable to governed source data and transformation logic.Design governed master and reference data structures for property/SBU, legal entity, department, cost centre, account, financial hierarchy, reporting hierarchy, calendar/period and currency.Implement mapping, harmonisation, survivorship and exception-management rules across heterogeneous source systems.Establish ownership and stewardship for master/reference entities and incorporate mastered business entities into the Ontology.Build enterprise-grade Palantir reports, dashboards and analytical experiences for Corporate Finance and business units.Develop reusable reporting datasets and consistent KPI definitions for trend, variance and comparative analysis.Enable executive and management analysis across Finance and approved operational data domains.Automate recurring Finance reports, BRM packs, management templates, presentations and Excel outputs using governed Foundry data.Build reusable components for scheduled or event-driven reporting workflows.Develop automated analytical narratives and commentary based on validated financial results.Build an AI and context layer on top of governed Finance datasets and Ontology.Develop conversational analytics enabling authorized users to query Finance data using natural language.Deliver AI-enabled data products for Finance Q&A, KPI exploration, variance analysis, trends, automated narratives and management reporting.Implement grounding, validation, explainability, access control, auditability and governance for AI-generated outputs.Knowledge, skills & experience:Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Engineering, Finance Technology or a related discipline.Typically 7+ years of relevant Data Engineering, Data Architecture or Analytics Engineering experience.Typically 2+ years of hands-on Palantir Foundry experience, with demonstrable delivery of production pipelines, datasets and Ontology solutions.Demonstrated experience delivering enterprise-scale Finance data and analytics solutions from requirements through UAT, deployment, handover and production support.Strong hands-on experience with Palantir Foundry datasets, pipelines, transformations and production deployment.Proven experience designing and implementing Palantir Ontology objects, properties, relationships, actions and security patterns.Experience with Foundry data products, lineage, governance, reporting/analytics and operational support.Strong proficiency in Python, PySpark / Apache Spark and SQL.Strong knowledge of ETL/ELT architecture, dimensional modelling, data lake/lakehouse patterns, APIs and enterprise integration.Experience with incremental processing, historical data, performance optimization, logging, testing and data reconciliation.Practical experience with General Ledger, P&L, Budget, Forecast, Actuals, Revenue, Expenses, EBITDA, cost centres, Chart of Accounts, financial hierarchies and management reporting.Experience with financial reconciliation and control frameworks.Experience with HFM or a comparable enterprise financial consolidation/planning platform is highly desirable.Strong understanding of lineage, metadata management, business glossaries, classification/tagging, MDM, reference data, data quality, ownership and stewardship.Experience with Generative AI, conversational BI, enterprise AI assistants, natural-language querying, semantic/context layers and AI-generated narratives.Knowledge of Microsoft Copilot or Microsoft AI Foundry is advantageous.Strong hands-on engineering and solution ownership.Ability to translate complex Finance requirements into robust technical designs.Financial and analytical thinking with strong attention to data accuracy and reconciliation.Strong stakeholder communication across Finance, business, architecture, governance and engineering teams.Structured problem solving, documentation discipline and ability to deliver in an evolving environment.Commitment to security, data governance, quality and operational excellence.