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We are Boeing Global Services (BGS) Engineering team creating and implementing innovative technologies that make the impossible possible and enabling the future of aerospace. We provide engineering design and support, including aftermarket modifications, and are innovating to make product and services safety even stronger. Join us and put your passion, determination, and skill to work building the future! #TheFutureIsBuiltHere #ChangeTheWorld
The Boeing Company is looking for Data Engineers to join our team in Seattle, Washington. This position supports the development and sustainment of cloud data infrastructure for the Safety Data Analytics (SDA) program in Boeing Global Services (BGS) Training, Digital & Analytics (TD&A). The position will be fully on-site.
Our teams are currently hiring for a broad range of experience levels including; Mid-Level and Senior Data Engineers.
In this role, you will be part of a growing team of Data Engineers that is working to build and maintain data infrastructure that processes large amounts of commercial airplane flight data, making curated datasets available for data consumers through a Delta Lake in Azure Databricks and a data warehouse in Google Cloud BigQuery. You will partner directly with Architects, Data Scientists, Software Developers, and Business Intelligence Analysts to define technical requirements for highly scalable streaming and batch data pipeline features; then you will design, implement, test, and support these features. An attention to detail and obsession with quality is a must, because the data products that our Data Engineering team produces serve both internally facing and externally facing applications.
A successful candidate will be a self-starter who understands the importance of collaborating with partner teams to fully define functional requirements before starting technical work. This role requires prior experience managing and analyzing data at scale in Azure Databricks and/or Google Cloud Platform (GCP) along with a dependable aptitude for Python/Spark, Containers, and DevOps to deliver scalable Cloud Data Engineering solutions. Prior experience managing and analyzing aerospace flight data (QAR/CPL, CVR/FDR, and/or ADS-B) at scale is highly desirable. Candidates with ETL and workflow orchestration in both GCP and Azure Databricks are desired, as our team will support an existing container-based GCP data infrastructure until our migration to Azure Databricks is complete.
The Safety Data Analytics program is a multi-disciplinary team of data professionals, Analytical Insights Managers, and Pilots who work together to identify and communicate data-driven insights to external aerospace customers, with the end goal of making flying safer. Join us, as our Data Engineering team creates a new generation of scalability and efficiency for data consumers in an Azure Databricks Delta Lake.

BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE):

• 5+ years of related work experience
• 3+ years of experience developing Python scripts, packages, and notebooks to analyze and process large datasets
• 3+ years of experience developing complex SQL queries to interact with relational datasets
• 2+ years of experience working in Azure, Google Cloud Platform, or Databricks
• 1+ years of workplace experience using Apache Spark, Apache Beam, and/or Dask for distributed processing of large, cloud-based datasets
• Ability to support our global customer base with a flexible work schedule which may include late or early meetings

PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE):

• 7+ years of related work experience or an equivalent combination of technical education and experience
• Education/experience typically acquired through advanced technical education (e.g. Associates or Bachelor)
• 3+ years of experience using Git for version control of software
• 2+ years of experience modeling, developing, and maintaining SQL or NoSQL datastores and maintaining analytics datastores (Databricks Delta Tables or Google BigQuery preferred)
• 2+ years of experience developing and maintaining ETL workflow orchestration using tools like Apache Airflow, GCP Workflows, or Databricks Workflows
• 2+ years developing and maintaining CI/CD pipelines
• 1+ years of experience with PySpark or Scala
• Experience working with aerospace datasets including timeseries flight data (QAR/CPL, CVR/FDR, and/or ADS-B) at scale is highly desirable
• Experience working in a role that develops Data Engineering solutions as part of a cross-functional team that includes Data Engineering, Data Science, Software Engineers, and/or Business Intelligence Analysts

• Support the development and improvement of streaming, batch data pipelines in Azure Databricks and/or Google Cloud Platform to provide curated datasets of airplane flight data to partner teams
• Partner with internal stakeholders to define desired user experiences with data; use these requirements to design orchestration strategies, data models, and partition strategies that optimize performance and cost of data curation and access
• Use Python, PySpark, and/or Scala to programmatically analyze, reduce, transform, and load datasets that are too large for in-memory, computer-based workflows
• Develop Extract, Transform, Load (ETL) and analytics processes that consume data from: (1) unstructured files and sources, (2) SQL / NoSQL datastores, and (3) messaging queues / streams
• Develop and maintain CI/CD pipelines used to automate DevOps tasks
• Build, test, and deploy container workers for serverless, scalable ETL workflow orchestration
• Implement testing and alerts that identify undesirable performance in codebases and data pipelines
• Analyze large, cloud-based datasets to identify, disposition, and explain the root cause for unanticipated data trends
• Develop and maintain partnerships while working in a cross-functional team of Data Engineers, Data Scientists, Software Developers, and Business Intelligence Analysts
• Implement access-control and security systems for compliance with data governance policies
• Exercise critical thinking and innovative problem solving
• Ensure commitments and service levels are achieved or exceeded
• Demonstrate the Boeing Behaviors in a deliberate and observable way
• Occasional travel may be required