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We are looking for an experienced Data Engineer to specialize in aviation data and analytics, focusing on two critical areas: scalable and efficient processing of flight test data for rapid design iteration and near-real-time analysis of aircraft health data for predictive maintenance. This role is vital for accelerating our aircraft design and improvement processes through efficient, scalable data processing and for ensuring operational reliability and safety through advanced predictive analytics.
Job Responsibility:
Architect, build, and optimize our data processing systems to ensure reliability, efficiency, and scalability
Develop and optimize ETL processes, data models, and data architectures for data transformation, structures, metadata, and workload management
Develop and maintain data models that support analytics, reporting, and custom app development
Create robust data quality observability, monitoring, testing, and validation frameworks
Engage actively with analytics teams and business stakeholders to understand their data needs, ensuring the data architecture supports decision-making processes effectively
Support the integration of data systems with aircraft telemetry, flight testing, and operational systems
Requirements:
Bachelor’s or Master’s degree in Computer Science, Aerospace Engineering, Data Analytics, or a related field
At least 3 years experience in data or software engineering with background implementing best practices for SQL and programming languages (e.g. Python, Go, Rust)
Experience designing and managing data warehouse / lakehouse architectures for high performance and low latency
Led development of real-time data pipelines using Kafka or related technologies
Expertise with one or more cloud data platforms (e.g., AWS, GCP, Azure)
Deep understanding of data security and quality governance
Deployed and scaled data workloads using Docker and Kubernetes, with the ability to manage compute resources for high-volume processing
Familiarity with ERP systems and how to extract data to build custom tools & applications
Knowledge of integrating Gen AI into production data workflows
Exceptional analytical skills, attention to detail, and the ability to collaborate effectively across multidisciplinary teams
Clear communication skills that are essential for working across diverse stakeholders
Nice to have:
Solid foundation in machine learning and other data science fundamentals
Familiarity with time series data applications and related technologies
Experience with Infrastructure as Code (Terraform, CloudFormation)
Advanced skills in predictive analytics and machine learning models for maintenance and anomaly detection
Experience in aerospace or a related field, particularly with flight test data analysis and aircraft health monitoring