Senior Software Developer – Data Engineer

at  Boeing

At Boeing, we innovate and collaborate to make the world a better place. From the seabed to outer space, you can contribute to work that matters with a company where diversity, equity and inclusion are shared values. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
Boeing Defense, Space and Security (BDS) is seeking a Senior Software Developer – Data Engineer to support our dynamic team in Seattle, WA.
At Boeing, we are all innovators on a mission to connect, protect, explore, and inspire. From the seabed to outer space, you’ll learn and grow, contributing to work that shapes the world. Find your future with us.
ICE and PIVT enable production teams to manage work statements, optimize labor charging, and proactively address non-conformances. This leads to improved shop floor execution, enhanced performance visibility, and data-driven decision-making. Additionally, these applications empower supporting functions such as production engineering by providing necessary data and insights to optimize processes, identify bottlenecks, and drive continuous improvement initiatives. Ultimately, ICE and PIVT enable teams to meet production targets, improve quality, and foster a culture of ongoing improvement.

BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE):

• 5+ years of experience writing software for data services
• 5+ years of experience with SQL development
• 5+ years of experience with ETL programming
• 5+ years of experience developing data pipelines
• 5+ years of experience developing software products in a cloud environment

PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE):

• Bachelor’s degree in a technical field (Master’s or Doctorate preferred).
• Experience in a manufacturing or aerospace environment.
• Experience in data analytics.

TYPICAL EDUCATION / EXPERIENCE:

Education/experience typically acquired through advanced technical education (e.g. Bachelor) and typically 9 or more years’ related work experience or an equivalent combination of technical education and experience (e.g. PhD+4 years’ related work experience, Master+7 years’ related work experience, 13 years’ related work experience, etc.)

• Drives the vision for data foundation and analytics, accelerating the building and improvement of cross-platform components.
• Conceptualizes and owns the data architecture for multiple large-scale projects, evaluating design and operational cost-benefit tradeoffs.
• Leads the design, development, and maintenance of complex and scalable data pipelines, extracting, transforming, and loading data from diverse sources.
• Provides technical leadership and mentorship to a team of data engineers, ensuring best practices, code quality, and professional development.
• Builds cross-functional relationships with Data Scientists, Product Managers, and Software Engineers to understand and deliver on data needs.
• Defines and manages SLA for all data sets in allocated areas of ownership.
• Determines and implements security models based on privacy requirements, ensuring compliance with safeguards and addressing data quality issues.
• Architects and implement end-to-end data integration, ETL, and data processing solutions aligned with business goals.
• Optimizes and tunes data pipelines for maximum performance, scalability, and reliability.
• Designs, builds, and launches collections of sophisticated data models and visualizations supporting various use cases.
• Solves challenging data integration problems using optimal ETL patterns, frameworks, and query techniques.
• Optimizes pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.
• Influences product and cross-functional teams to identify data opportunities for driving impact.
• Applies proven expertise to build high-performance scalable data warehouses.
• Designs, build, and launches efficient & reliable data pipelines to move and transform data.
• Sources external data securely from numerous partners.
• Designs data models intelligently for optimal storage and retrieval.
• Deploys inclusive data quality checks to ensure high-quality data.
• Optimizes existing pipelines and maintain all domain-related data pipelines.
• Takes ownership of the end-to-end data ecosystem.
• Collaborates with infrastructure and DevOps teams to ensure the availability, security, and efficiency of data platforms.
• Drives the adoption of modern data management practices, tools, and technologies within the organization.