Data Engineer

• Support a broad set of architectural needs across multiple workstreams
• Design and own the data layer behind GenAI, RAG, and Agentic AI applications
• Ensure enterprise data and knowledge are ingested, prepared, stored, governed, and made available for AI consumption and retrieval
• Own and design data architecture, data modeling, ingestion, and platform modernization for enterprise Azure environments
• Design and implement scalable, metadata/configuration-driven data ingestion and data platform solutions
• Work with structured and genuinely unstructured data across the enterprise platform
• Modernize existing data platforms and ensure implementation-ready architecture

Senior Azure Data Architect – GenAI, RAG, Agentic AI

• Design, implement and maintain integrations between SCADA, plant systems, historians, monitoring platforms and enterprise solutions
• Manage OT/IT interfaces and industrial communications using OPC UA, Modbus and MQTT, including tag mapping, naming conventions and plant-edge data standardization
• Administer or coordinate industrial historians and time-series platforms, ensuring appropriate data collection, availability, retention and retrieval
• Monitor data pipelines and interfaces, identifying missing, delayed or inconsistent data and resolving protocol, connectivity and integration issues
• Define and apply standards for data quality, metadata, asset hierarchies and technical documentation across countries and technologies
• Support onboarding of new and acquired assets, including integration requirements, commissioning data and interface validation
• Coordinate technical activities with EPCs, OEMs, O&M providers and digital platform vendors
• Work with OT Technology Assurance, Operational Asset Reporting and IT Data & Analytics to ensure operational data is fit for reporting and analytics
• Act as the technical bridge between OT, IT, Asset Management and technology partners, strengthening internal ownership of the OT data integration layer

OT Integration, Data Engineer

• Deliver new reporting and analytics solutions supporting business-critical reporting requirements
• Partner with business stakeholders and analysts to translate reporting needs into scalable technical solutions
• Maintain, enhance, and optimize reporting datasets, SQL queries, data models, and reporting performance
• Support migration and modernization of reporting solutions from legacy BI platforms to Tableau and other modern technologies
• Build and improve data pipelines, analytical datasets, and reporting structures supporting management reporting, KPIs, and self-service analytics
• Contribute to reporting governance, data quality, lineage, controls, and consistency across reporting outputs
• Help shape future reporting architecture as the organization continues its data and analytics transformation journey

Data Engineer – Reporting & Analytics

• Propose and build data-driven product features such as market and competitor intelligence, pricing benchmarks, contracting-body profiles, tender matching, alerting, and data-quality signals
• Own the data side of AI features
• Design and improve the retrieval layer behind Vera and the Dynamic RAG service, including document ingestion, conversion, chunking, embeddings, Qdrant indexing, Elasticsearch hybrid search, and reranking
• Use LLMs for structured extraction, classification, entity resolution, and summarisation
• Build evaluation sets to measure retrieval and answer quality
• Provide clean, structured, documented data and tools for Vera and the Tendios MCP server
• Define and measure data and retrieval quality, including source coverage, freshness, parsing accuracy, deduplication, and RAG answer quality
• Own and improve the collection pipeline, including Crawl Manager, Tenders Discovery, Collector, parsers, and RabbitMQ consumers
• Improve pipeline reliability, observability, and cost efficiency
• Maintain consistent read models in Elasticsearch and Qdrant
• Build the analytics layer on ClickHouse, orchestrated with Prefect and exposed through Metabase
• Replace manual Excel-based SaaS metrics reporting with a warehouse for MRR, churn, and NRR
• Write production Python for pipelines and data services
• Write TypeScript/Node.js in the NestJS Turborepo backend where data features touch the API
• Review code, set standards for data modelling and migrations, and document decisions in Confluence
• Contribute to data governance and security work related to ENS and ISMS compliance
• Report directly to the Head of Technology and collaborate with product, AI & Data, and backend squads

Senior Data Engineer

• Own the discovery and access side of Agilent's scientific data platform
• Define the target state and roadmap for scientific data discovery and access
• Establish catalog and access behavior, service boundaries, contracts, integration patterns, and the path between them
• Own and version catalog records, subgraph boundaries, data service views, and event schemas
• Define authoritative systems under data governance rules
• Design controlled, provenance-aware access paths for AI agents
• Review integrations against contracts and participation requirements
• Design modernization paths for legacy sources, including on-premises, hybrid, and cloud transitions
• Set query and index performance targets
• Design pipelines keeping catalogs, search indexes, and access views current, including backfill and recovery
• Work directly with engineering on designs, implementation plans, and delivered work
• Create decision records and diagrams and explain tradeoffs to technical and business stakeholders
• Work with .NET/C#, Angular, federated GraphQL, PostgreSQL, Oracle, SQL Server, RabbitMQ, Kubernetes, Helm, Windows installers, S3-compatible storage, and scientific data formats

Senior Data Architect, Scientific Data Platform

• Diseñar e implementar soluciones sólidas sobre la plataforma de datos corporativa
• Garantizar la integración y adopción de capacidades tecnológicas entre las áreas de Negocio e IT
• Prestar soporte técnico especializado a los equipos de desarrollo y asegurar el cumplimiento de los SLA
• Diagnosticar y resolver incidencias complejas de nivel avanzado
• Atender consultas funcionales y técnicas sobre los activos de datos
• Dirigir la adopción, puesta en marcha y operación de servicios corporativos de IA sustentados en Palantir Foundry
• Guiar la evolución continua del entorno mediante nuevas capacidades tecnológicas
• Automatizar procesos operativos y tareas de despliegue para maximizar la eficiencia y optimizar la experiencia de los desarrolladores

Data Platform Engineer

• Follow the training for a clear understanding of the guidelines related to the different reporting and specific requirements associated to the reporting.
• Access the fundcraft’s platform, and review the data collected in the context of the preparation of the reports.
• Identify any missing mandatory data and liaise with the relevant team.
• Ensure the completeness of the report and data accuracy.
• Escalate any issues to the team leader.
• Organise the work to avoid any delays in the sendings.
• Ensure appropriate access on third-party portals to facilitate reporting submissions.
• Report activity to the team leader via a monitoring dashboard.
• Support and partner with the team in day-to-day duties related to transmission of reporting to third parties.
• Facilitate production of reports covering fund administration activities, ensuring timely and accurate internal and external communications.

Junior Data Engineer

• Work on strategic data initiatives
• Build and operate reliable, scalable data products on clients’ Palantir-based data platform
• Design, build, and maintain scalable data pipelines and data products using Palantir
• Develop data transformations using Python and PySpark
• Build robust ETL/ELT workflows integrating multiple data sources
• Write efficient SQL for data transformation and analytics
• Design and maintain data models optimized for analytical use cases
• Collaborate with business and analytics stakeholders to translate requirements into data solutions
• Ensure data quality and reliability through testing, monitoring, and CI/CD
• Analyze data to identify inconsistencies and improvement opportunities
• Document solutions and contribute to data engineering best practices

Senior Data Engineer, Palantir focus

• Diseñar, desarrollar y testear soluciones data alineadas con las necesidades de negocio
• Investigar nuevas tecnologías y algoritmos, desarrollando prototipos y PoC (Proof of Concept)
• Trabajar en un equipo multidisciplinar junto a Data Scientists, Software Architects y Developers
• Proporcionar puntualmente soporte técnico al departamento de ventas
• Desarrollar herramientas analíticas y programas
• Desarrollar y procesar sistemas de datos
• Desarrollar algoritmos y prototipos

• Diseñar, construir y mantener pipelines de datos escalables ETL/ELT
• Contribuir al diseño y construcción de la plataforma de datos cloud de DWS basada en Snowflake
• Apoyar la migración desde sistemas legados on-premise hacia la nube
• Trabajar con arquitectos de datos, analistas de negocio y equipos de reporting para modelar, validar y disponibilizar datos
• Desarrollar y mantener controles de calidad, monitorización y observabilidad de pipelines
• Colaborar con DevOps en pipelines CI/CD, infraestructura como código y despliegues automatizados
• Aplicar buenas prácticas de linaje, catalogación y gobierno del dato
• Analizar y resolver incidencias de producción relacionadas con datos
• Optimizar el rendimiento de pipelines y cargas de trabajo del data warehouse cloud
• Contribuir a estándares técnicos y buenas prácticas de ingeniería dentro del equipo Data Platforms