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$159,500–$219,150.
Based on 240 similar postings.
Employer
About Airbus
Airbus is a leading global aircraft manufacturer and aerospace company producing commercial jets (A320, A350, A380), military aircraft, helicopters, and space systems for customers worldwide. Industry: Aerospace & Aviation Manufacturing
Lead Data & Analytics – AI & Advanced Analytics joins the AI and Advanced Analytics team to develop cutting-edge machine learning, enterprise data architecture, and advanced analytics applications. The role involves designing and maintaining robust end-to-end data pipelines within Palantir Skywise, managing platforms like Alteryx and Tableau, and translating complex manufacturing and supply chain challenges into technical requirements. You will build and deploy generative AI models, manage MLOps pipelines, and provide technical leadership by mentoring junior developers and establishing governance standards. Key technologies include Python, PySpark, SQL, Spark SQL, and the Palantir ecosystem, including Pipeline Builder, Workshop, Slate, and AIP Assist. The role addresses critical aviation manufacturing hurdles, aiming to optimize assembly line efficiency and operational decision-making across commercial aviation and helicopter divisions by transforming physical production data into scalable technical assets.
Design and maintain scalable end-to-end data pipelines and analytical workflows within the Palantir Skywise platform.
Act as the primary technical authority for data engineering and Palantir Skywise across North American operations.
Translate complex manufacturing, logistics, and supply chain challenges into technical requirements and actionable data products.
Build and deploy advanced AI applications, including generative AI models and machine learning pipelines, into production workflows.
Manage and optimize enterprise analytics platforms such as Alteryx and Tableau to ensure high performance and low latency.
Lead technical workshops and mentoring sessions to improve AI and data literacy across regional work sites.
Establish data governance standards, security protocols, and development best practices for the engineering team.
What we're looking for
Minimum 10 years of experience in data engineering, advanced analytics, or business intelligence (or 7+ years with a Master's degree).
Bachelor’s degree in Computer Science, Data Science, Business Analytics, Engineering, Information Systems, or a quantitative field (Master’s preferred).
3+ years of hands-on experience in the Palantir Skywise ecosystem including Pipeline Builder, Workshop, Slate, and AIP Assist.
Advanced technical proficiency in Python, PySpark, SQL, and Spark SQL to build performant data pipelines.
Proven experience with GenAI models, prompt engineering, agentic workflows, and deploying AI/ML models into production.
Expert knowledge of enterprise BI tools including Tableau, Alteryx, and PowerBI.
Demonstrated track record leading digital initiatives in aerospace, manufacturing, transportation, or complex operational environments.