Senior Data Engineer (Enterprise Services)

Senior Data Engineer (Enterprise Services)

Company:

The Boeing Company

Boeing’s Enterprise Services organization is seeking a Senior Data Engineer to support our transformation journey. You will be joining our Enterprise Services Technology and Systems Data Management team. Enterprise Services is a team of 2,500+ employees whose collective mission is to enable the build of Boeing’s products. Enterprise Services provides strategic partnership and support to all Boeing business units through multiple service towers – creating outsized impact and value across the Enterprise.

Up to 20% travel may be required to other U.S. Boeing sites.

Position Responsibilities:

• Work with the Enterprise Services and Data Management Office leadership team to build complex, detailed visual displays and stories out of data to drive actionable outcomes

• Assemble large and complex sets of industrial data and utilize the data pipeline and data infrastructure to meet functional business requirements

• Build out new platform integrations within Boeing or with our partners or vendors to support the organization’s growing data volume and complexity

• Identify and implement internal process improvements aimed to achieve greater scalability, optimizing data delivery, and automating existing manual processes

• Build required infrastructure for optimal extraction, transformation and loading (ETL) of data from various data sources using Google Cloud Platform (GCP) and SQL technologies

• Understand data modeling concepts and best practices while working with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data related technical issues

• Support Master Data Management initiatives by building and maintaining the technical infrastructure that enables consolidation, cleansing, and standardization of master data from various sources across the organization, ensuring a single source of truth

• Build and improve data-driven models and analytical tools that provide information to downstream business intelligence tools providing actionable insight into key business performance metrics including operational efficiency and asset performance management

• Actively implement processes and tools to monitor data quality ensuring high data integrity and availability to key stakeholders

• Work closely with a team of frontend and backend engineers, product managers, analysts, business units and engineering teams to develop a resilient strategy for long term data platform architecture

• Follow industry best practices for documentation of standards, processes and data architecture for future reference and compliance

• Implement data storage solutions, including data lakes and warehouses

Key Relationships & Stakeholders:

• Enterprise Services Executive Leadership Team

• Data Science and IT; Finance

• Service Tower Leadership (Indirect Supply Chain, Real Estate, Facilities & Asset Management, Executive Flight)

• External vendors and/or consultants

Basic Qualifications (Required Skills/Experience):

• Bachelor's degree or higher in computer science, engineering, information technology, or a related discipline

• 5 + years of experience in data and/or business analytics & related BI tools (e.g., Cognos, Microsoft Power BI, Tableau, etc.)

• 5+ years of experience with SQL and SQL & NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB)

• Proficiency in programming languages (Python)

• Experience with data modeling, data warehousing solutions (e.g., Amazon Redshift, Google BigQuery) and data governance principles

• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform)

• Knowledge of big data technologies (e.g., Hadoop, Spark)

Preferred Qualifications (Desired Skills/Experience):

• 10+ years of related work experience or an equivalent combination of education and experience

• Master's degree

• Experience working on large scale complex programs focused on data integration

• Experience delivering business and data analytics solutions in a manufacturing, engineering, or operations environment

• Experience presenting to various levels within an organization regarding different data sets, fields, taxonomy, reporting suites, platforms, data systems, and system architecture

• Possess a continuous improvement mindset

• Problem solving skills and attention to detail

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