Palantir Data Engineer

Driving the delivery of enterprise-wide data capabilities, the Palantir Data Engineer occupies a critical position in shaping scalable, data-centric solutions that underpin business insights and operational efficiency. This role exists to design, develop, and maintain robust data pipelines and integration workflows primarily leveraging Palantir Foundry alongside complementary analytics platforms, ensuring organizations can harness data from diverse domains such as digital transformation, ERP systems, customer experience, finance, and operations. The impact of this position lies in enabling seamless data accessibility and governance compliance, empowering decision-makers with high-quality, timely information that drives strategic objectives and enhances overall business performance.

The Palantir Data Engineer undertakes responsibility for crafting and sustaining complex data ecosystems that support cross-functional initiatives and long-term technology strategies. Daily tasks involve translating business requirements into actionable data models, optimising ETL processes, and actively improving performance across data platforms. Ensuring data governance, security protocols, and metadata accuracy remains an ongoing focus, alongside providing advanced analytical capabilities to facilitate predictive insights and machine learning applications. Collaboration forms a key element of this role, requiring close engagement with business analysts, data scientists, and various operational teams to maintain consistent, reliable data flows that meet enterprise standards.

Working within an environment that combines cutting-edge data management technologies, the Palantir Data Engineer utilises Palantir Foundry as the core platform for data transformation and integration. Complementing this, Power BI is employed for data visualisation and analytics, enabling the delivery of dashboards and reports that translate raw data into meaningful, actionable insights. The role demands a technical foundation in cloud-based data platforms, ETL, and automation, supplemented by an understanding of performance tuning, data security, and metadata management to guarantee system reliability and scalability. An openness to adopting emerging tools and technologies in BI, AI, and data engineering further enhances the ability to innovate and continually improve.

The position requires a hybrid working arrangement, with a commitment of four days onsite and one day remote each week, accommodating both collaborative project work and focused individual tasks. This permanent role is well-suited to candidates seeking to apply their expertise within a manufacturing context that is leveraging data-driven transformation to refine operational delivery and business insights across multiple domains. Responsibility extends to individual contribution within cross-functional teams, working alongside vendor partners and subject matter experts to align data initiatives with wider organisational goals.

Candidates will bring at least five years of experience in data engineering or business intelligence development, with hands-on proficiency in Palantir Foundry, Power BI, and related technologies such as Azure cloud services. A solid grasp of data modelling, ETL techniques, and performance optimisation forms the technical backbone required. Additionally, expertise in data governance, metadata management, and data security principles is essential to maintain high standards of data quality and compliance. Experience or familiarity with machine learning models and automation frameworks will be advantageous, supporting analytical sophistication and innovation within the role.

Success in this role depends on driving execution with discipline, adapting to change in a dynamic technology landscape, and maintaining a customer-focused approach in delivering solutions that meet stakeholder needs. The Palantir Data Engineer plays a vital role in facilitating data accessibility that enhances operational efficiency and strategic decision-making, while contributing to the ongoing modernisation and transformation of enterprise data capabilities.

This position sits firmly within the machinery manufacturing sector, offering the chance to engage with complex data challenges across a broad industrial environment where innovation and process optimisation are key drivers of competitive advantage.