{"id":2208640,"url":"https://alion.io/job/airbus-data-analyst-digital-workplace","title":"Data Analyst – Digital Workplace","company":{"id":3100,"name":"Airbus","domain":"airbus.com","url":"https://alion.io/company/airbus","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":96,"open_postings":233,"ghost_share":0,"stale_share":0.322,"repost_share":0.039,"time_to_fill_p50_days":20,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Analytics","role_family":"Analytics","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":12500,"max_usd":29000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1415},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"FinOps","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"QlikSense","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Self-Healing","optional":false},{"name":"ServiceNow","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Vertex AI","optional":false},{"name":"ITIL","optional":true},{"name":"Kanban","optional":true},{"name":"Scrum","optional":true},{"name":"SLI/SLO/SLA","optional":true}],"status":"live","first_seen_at":"2026-10-09T00:00:00Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-13T00:57:11Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Job Description:\nAirbus 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.\nA 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.\nAirbus 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.\nDescription:\nDigital 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. \nDigital Workplace consists of the following core elements: Operational Performance, Devices and Services, Employee Collaboration, Industrial and Specialist Devices, Workplace Support, User Adoption.\nWe 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.\nPosition Summary:\nThe 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.\nThe 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.\nQualification & Experience:\nWe 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.\nAre you ready to share this exciting challenge with us?\nEducation: Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Applied Mathematics, Statistics, or a related quantitative field.\nExperience: 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.\nCertifications: At least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer, AWS Certified AI/ML Specialist, or equivalent credentials).\nPlatform Expertise: Proven track record using Skywise / Palantir Foundry, AWS/GCP cloud platforms, and ServiceNow operational environments.\nProven 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.\nAdvanced proficiency in Python, SQL, React, JavaScript, and CSS. and strong understanding of REST APIs andBig Data architectures.\nAdvanced analytical expertise in data modeling, database management, and SQL (expert level).\nExperience with BI tools, Google Data Studio, and BigQuery.\nProficient in data acquisition, automation, and maintaining data systems from multiple sources.\nAbility to identify valuable data sources and optimize data collection processes and Strong analytical mindset with exceptional attention to detail and accuracy.\nAbility to help transform organizational reporting processes through automation and optimization.\nKey Requirements and Responsibilities:\nEnd-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.\nDevelop, test, document, and deploy data pipelines, analytical models, and visualization tools to support strategic and operational initiatives.\nWork with Product Owners and core Airbus business functions to capture requirements, understand business processes, and deliver impactful data-driven solutions.\nManage the full application delivery lifecycle - from design and implementation to testing, deployment, and support.\nBuild and maintain pipelines to enable automated deployments across Development, QA, and Production environments.\nTroubleshoot and resolve application issues, manage incidents and requests, and provide ongoing support for developed tools.\nEncourage and enable self-service analytics by empowering business teams and promoting data literacy.\nCoach and develop data analytics awareness among internal customers and stakeholders.\nDefine, implement, and maintain KPI metric reports, dashboards, and performance analytics (PA) reporting.\nHelp automate reporting processes and transform the organization’s approach to data management.\nAcquire data from various sources, manage and maintain data systems, and automate data collection processes.\nEnsure compliance with best practices in data quality, security, and governance.\nBehavioral 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).\nIntelligent 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.\nPipeline & Feature Store Management: Feature-engineer unstructured datasets from ServiceNow, telemetry (Workblaze/DEX), and enterprise systems into robust data pipelines across Dev/QA/Prod environments.\nGovernance & FinOps: Ensure compliance with Airbus data governance, privacy, security frameworks, and ethical AI standards while tracking model inference costs and API spend.\nTechnical Essentials:\nProgramming & Data Wrangling: Mastery of Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow) and expert-level SQL for querying and transforming large-scale datasets.\nCloud & 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).\nGenerative 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).\nMLOps & DevOps: Hands-on experience with REST APIs, Docker, Kubernetes, CI/CD pipelines, and automated model deployment/monitoring workflows.\nBI & Visualization: Proficiency in Qliksense, Looker Studio, Workshop, or Performance Analytics dashboards to present predictive insights to stakeholders.\nSoft Skills & Behavioural Attributes: \nStrategic Mindset & ROI Focus: Ability to translate complex business problems into viable AI use cases with tangible ROI and operational impact.\nCommunication & Storytelling: Exceptional skills in explaining complex machine learning models, statistical findings, and predictions to non-technical business leaders.\nAdaptability & Problem-Solving: Thrives in dynamic environments, demonstrates strong curiosity, attention to detail, and a passion for continuous learning.\nCross-Functional Collaboration: Ability to work effectively with Product Owners, Agile delivery teams, L1/L2 support units, and European leadership.\nGood to Have:\nFamiliarity with Digital Employee Experience (DEX) metrics and telemetry tools (Workblaze / Nexthink).\nExposure to source-to-source code parsing, AST analysis, or automated design document generation utilities.\nExperience with ITIL frameworks, SAFe / Agile Scrum delivery methodologies, or ServiceNow portal development.\nFluency or working proficiency in French or German in addition to mandatory English fluency.\nCoach internal business users with a goal of being largely self-sufficient for their analytics needs\nResearch and document new and improved features on existing tools \nBecome familiar with new analytics technologies in Airbus and in the marketplace\nStay current on latest analytics trends and emerging technologies \nRecommend new ways of using tools to further business needs\nUser experience oriented\nFluency in English is mandatory, French or German knowledge will be an added advantage \nWorking experience in Agile Scrum, SAFe and/or Kanban projects\nSuccess Metrics\nSuccess will be measured in a variety of areas, including but not limited to\nModel Accuracy & Deployment: Successful high-accuracy deployment and adoption of predictive models in production with low latency and high uptime.\nOperational & Cost Impact: Measurable cost savings and waste reduction via operational anomaly identification and SLA breach prevention.\nOn-Time Quality Delivery: Consistently delivering first-time-right AI/ML initiatives throughout the complete lifecycle.\nStakeholder Satisfaction: Satisfaction scores and strong collaboration feedback across Airbus Digital Workplace leadership and European product units.\nBring innovative cost effective solutions\nAchieve the customer satisfaction\nAbility to handle a subject from demand management, to development and support\nAbility to understand the business potential of applications and provide insight to clients\nThe role will also have the following key outputs:\nStrong link with all the Airbus Digital Workplace services\nProactive in providing guidance & inputs for the Airbus Digital Workplace strategic roadmap\nThis job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.\nThis job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.\nCompany:\nAirbus India Private LimitedEmployment Type:\nPermanent-------\nExperience Level:\nProfessionalJob Family:\nDigital By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.\nAirbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.\nAirbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. 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