Data Analyst – Digital Workplace

Job description

Job Description: Airbus is an international pioneer in the aerospace industry. We are a leader in designing, manufacturing and delivering aerospace products, services and solutions to customers on a global scale. We aim for a better-connected, safer and more prosperous world. A commercial aircraft manufacturer, with Space and Defense as well as Helicopters Divisions, Airbus is the largest aeronautics and space company in Europe and a worldwide leader. Airbus has built on its strong European heritage to become truly international – with roughly 180 locations and 12,000 direct suppliers globally. The company has aircraft and helicopter final assembly lines across Asia, Europe and the Americas, and has achieved a more than sixfold order book increase since 2000. Description: Digital Workplace (DW) was established to be an enabler of Digital Transformation across Airbus. Its primary focus is to: provide employees with simple, intuitive and easy to use workplace tools and services; enable employees to create and collaborate from anywhere at any time; enable continuous optimisation of work experience and productivity underpinned by fit-for-purpose security. Digital Workplace consists of the following core elements: Operational Performance, Devices and Services, Employee Collaboration, Industrial and Specialist Devices, Workplace Support, User Adoption. We are currently looking for a new colleague mastering data analysis and tooling to join the Operational Performance PSL (DWW). His/Her expertise will support us to bring data to life. Thus we will make the right decisions in the product design and at project steering and also we will have all the information required to transform and to improve user experience. Position Summary: The Data Analyst will play a key role in designing, developing, and deploying scalable data solutions within the Skywise / Palantir Foundry platform or other equivalent platforms to support Airbus divisions and functions across Europe. This position combines strong analytical, technical, and communication skills to drive business value through data insights and automation. This position bridges quantitative data analysis, software engineering, and applied artificial intelligence to transform operational datasets into proactive, actionable insights and automated enterprise solutions. Operating within the Skywise / Palantir Foundry framework, Cloud environments (AWS/GCP), and ServiceNow, you will architect, build, and deploy production-grade predictive algorithms, machine learning models, Generative AI capabilities, and interactive operational tools to empower business decision-making across Airbus divisions globally. The specialist will work closely with business and technical teams to identify opportunities for improvement through data value analysis, develop end-to-end analytics solutions, and promote data-driven decision-making across the organization. Qualification & Experience: We seek out curious minds. We value attention to detail, and we care deeply about outcomes. We are looking above all for passionate people, eager to learn, willing to share, establishing innovative ways of working and influencing culture change. Are you ready to share this exciting challenge with us? Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Applied Mathematics, Statistics, or a related quantitative field. Experience: 4 to 7 years of hands-on experience in building, deploying, and scaling end-to-end data pipelines, predictive models, machine learning solutions, and software automation systems. Certifications: At least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer, AWS Certified AI/ML Specialist, or equivalent credentials). Platform Expertise: Proven track record using Skywise / Palantir Foundry, AWS/GCP cloud platforms, and ServiceNow operational environments. Proven track record in developing and maintaining large-scale data applications on Foundry. Proficiency in Ontology Manager, Code Authoring, Contour, Workshop, and Data Ingestion modules. Experience in ETL scripting for data transformation. Advanced proficiency in Python, SQL, React, JavaScript, and CSS. and strong understanding of REST APIs andBig Data architectures. Advanced analytical expertise in data modeling, database management, and SQL (expert level). Experience with BI tools, Google Data Studio, and BigQuery. Proficient in data acquisition, automation, and maintaining data systems from multiple sources. Ability to identify valuable data sources and optimize data collection processes and Strong analytical mindset with exceptional attention to detail and accuracy. Ability to help transform organizational reporting processes through automation and optimization. Key Requirements and Responsibilities: End-to-End AI & Data Engineering: Design, build, evaluate, and deploy production-grade ML models and statistical solutions in Skywise/Foundry and Cloud platforms to transition from descriptive reporting to predictive/proactive analytics. Develop, test, document, and deploy data pipelines, analytical models, and visualization tools to support strategic and operational initiatives. Work with Product Owners and core Airbus business functions to capture requirements, understand business processes, and deliver impactful data-driven solutions. Manage the full application delivery lifecycle — from design and implementation to testing, deployment, and support. Build and maintain pipelines to enable automated deployments across Development, QA, and Production environments. Troubleshoot and resolve application issues, manage incidents and requests, and provide ongoing support for developed tools. Encourage and enable self-service analytics by empowering business teams and promoting data literacy. Coach and develop data analytics awareness among internal customers and stakeholders. Define, implement, and maintain KPI metric reports, dashboards, and performance analytics (PA) reporting. Help automate reporting processes and transform the organization’s approach to data management. Acquire data from various sources, manage and maintain data systems, and automate data collection processes. Ensure compliance with best practices in data quality, security, and governance. Behavioral Analytics & Anomaly Detection: Build behavioral engines to identify operational leakages (e.g., ghost asset detection, hardware failure modeling, supplier CMDB update lag, and usage anomalies). Intelligent Automation & Modernization: Design intelligent workflows, self-healing data scripts, and RAG-driven knowledge tools to automate domain-specific tasks and optimize IT Service Management processes. Pipeline & Feature Store Management: Feature-engineer unstructured datasets from ServiceNow, telemetry (Workblaze/DEX), and enterprise systems into robust data pipelines across Dev/QA/Prod environments. Governance & FinOps: Ensure compliance with Airbus data governance, privacy, security frameworks, and ethical AI standards while tracking model inference costs and API spend. Technical Essentials: Programming & Data Wrangling: Mastery of Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow) and expert-level SQL for querying and transforming large-scale datasets. Cloud & Platform Ecosystems: Deep proficiency in Skywise / Palantir Foundry (Ontology, Workshop, Contour) and Google Cloud Platform (Vertex AI, BigQuery, Cloud Run) or AWS (SageMaker, Bedrock, Lambda). Generative AI & Advanced ML: Experience with RAG architectures, vector databases (Pinecone, ChromaDB, Vertex Vector Search), LLM frameworks (LangChain/LlamaIndex), and core ML algorithms (Regression, Classification, Time-Series Forecasting). MLOps & DevOps: Hands-on experience with REST APIs, Docker, Kubernetes, CI/CD pipelines, and automated model deployment/monitoring workflows. BI & Visualization: Proficiency in Qliksense, Looker Studio, Workshop, or Perf