Data Engineer, Archer

• Bachelor’s or Master’s degree in Computer Science, Aerospace Engineering, Data Analytics, or a related field
• At least 5+ years of experience in data engineering, analytics, with demonstrated expertise in both batch and near-real-time data processing
• Proficient in data processing technologies (e.g., Hadoop, Spark, PySpark) and real-time data platforms (e.g., Apache Kafka, Flink, Spark Streaming)
• Strong understanding of SQL and programming languages (Python, Java, Scala) with a solid foundation in machine learning algorithms and other data science fundamentals
• Experience with cloud data platforms (e.g., AWS, GCP, Azure) and a deep understanding of data security and quality governance
• Exceptional analytical skills, attention to detail, and the ability to collaborate effectively across multidisciplinary teams
• Exceptional problem-solving abilities and attention to detail
• Excellent communication abilities, both in written and verbal form, are essential for effective collaboration with diverse teams

Desirable

• 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
• In this role, you will be tasked with various aspects of data engineering
• In addition to the above, your responsibilities will include but not limited to the following
• Architect and construct a comprehensive data warehouse, focusing on scalability, efficiency, reliability and solving business problems
• Engage actively with analytics teams and business stakeholders to understand their data needs, ensuring the data architecture supports decision-making processes effectively
• Develop and optimize ETL processes, data models, and data architectures for data transformation, structures, metadata, and workload management
• Implement and maintain robust data governance practices, ensuring data accuracy, compliance, and security
• Leverage big data technologies and tools for large-scale data processing and analytics
• Establish and oversee data quality monitoring and alerting systems to identify and rectify data inconsistencies and errors promptly
• Keep abreast of the latest trends in data engineering and big data technologies