Data Engineer

• Typically requires a University Degree or equivalent experience and a minimum of 8 years of prior relevant experience, or an Advanced Degree in a related field and a minimum of 5 years of experience.
• 5+ years of experience in data engineering or analytics engineering, preferably using Databricks or a similar lakehouse platform.
• Experience with SQL, Python, and Delta Lake.
• Experience with Unity Catalog, data governance, and data quality management.
• Experience building and maintaining data pipelines for machine learning training and inference.
• Experience with data modeling, classification schemas, and taxonomies.
• Extensive experience with data warehousing concepts, dimensional modeling, and ETL processes.
• Experience working in an Agile development environment and managing multiple priorities in a fast-paced environment.

• Experience with Microsoft Fabric, Delta Sharing, or cross-platform data sharing.
• Familiarity with annotation tools, natural language processing (NLP), and vector databases.
• Experience with MLflow or similar tools for experiment tracking and model management.
• Background in metrics and KPIs, information architecture, or IT and infrastructure domains.
• Strong analytical and problem-solving skills, with the ability to develop innovative solutions that improve business performance.
• Demonstrated leadership, interpersonal, and communication skills, including the ability to influence stakeholders and align teams toward common goals.
• Ability to manage multiple projects simultaneously while adapting to changing business and technical priorities.
• A flexible, collaborative mindset and the ability to thrive in a dynamic environment.

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market-leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.

The following position is to join our RTX Corporate, Enterprise Services team:

As a Data Engineer – Data & Insights, you will build and maintain the data foundation that powers analytics and AI capabilities across RTX. You will develop secure, governed, and consumption-ready data products while supporting machine learning workflows, data quality initiatives, and enterprise data integrations. Working collaboratively with data scientists, analysts, data owners, and business stakeholders, you will leverage modern data platforms and engineering practices to ensure data is trusted, well-structured, and accessible for business insights and advanced analytics.

• →Design, implement, and maintain data governance and architecture capabilities using Databricks Unity Catalog, including namespaces, permissions, lineage, and data access controls.
• →Implement automated data quality checks, monitoring, and alerts, coordinating remediation workflows with data owners and source teams.
• →Integrate data platforms with Microsoft Fabric and expose trusted Gold-layer data products through enterprise data marketplaces.
• →Develop and maintain reference architectures, data engineering standards, and technical documentation.
• →Build data annotation workflows and labeling interfaces in Databricks to support machine learning and AI initiatives.
• →Track annotation progress, data quality, and dataset versions to support reliable ML training and inference.
• →Develop LLM and Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, embedding generation, and vector search.
• →Support machine learning pipelines through feature engineering, batch and real-time scoring, and data monitoring.
• →Maintain MLflow capabilities for experiment tracking and model registry management.
• →Design and maintain data classification schemas, taxonomies, and labeling specifications for signals, severity levels, categories, and other business requirements.
• →Own and enhance key Gold-layer data products, including experience arrays and friction signal aggregates.
• →Integrate new data sources, implement business rules, and develop consumption-ready data views and APIs.
• →Maintain data dictionaries, product documentation, and metadata to support consistent data usage across the organization.
• →Collaborate with cross-functional teams in an Agile development environment to manage priorities, solve complex problems, and deliver scalable data solutions.

Click on this link to read the Policy and Terms

Please consider the following role type definition as you apply for this role: