Data Engineer III

Blue Origin•Huntsville, AL

27d

About The Position

At Blue Origin, we envision millions of people living and working in space for the benefit of Earth. We're working to develop reusable, safe, and low-cost space vehicles and systems within a culture of safety, collaboration, and inclusion. Join our team of problem solvers as we add new chapters to the history of spaceflight! This role is part of the Blue Origin Engines business unit, where our focus is the design, development, manufacturing, and testing of engines and propulsion systems. Built for multiple uses, our family of engines is powering the next generation of rockets for commercial, civil, national security, and human spaceflight. Join Blue Origin's exceptional team of visionaries, leaders, and problem-solvers who uphold a robust culture of safety. In this Level IIII position, you will play a key role in advancing space exploration by developing and managing sophisticated data architectures that ensure safe and repeatable space flight operations. Contribute to our mission of reducing the cost of access to space and helping realize Blue Origin's vision of millions of people living and working in space to benefit Earth. As a member within a highly skilled team, you will collaborate with data engineers, data scientists, system owners, product managers, and business leaders to architect and oversee the delivery of mission-critical, data-focused solutions for the Blue Origin Flight and Operations group. You will support initiatives across flagship programs including New Shepard, New Glenn, and Blue Engines, ensuring their strategic alignment and operational excellence through your technical expertise and collaborative approach. We are seeking a highly skilled Data Engineer who can facilitate cross-functional collaborations across business, engineering, and operations teams to optimize data management and analytics capabilities, driving Blue Origin's mission forward with innovative and scalable data solutions.

Requirements

Education: Bachelor's degree in Computer Science, Data Science, Information Systems, Aerospace Engineering, Mechanical Engineering, or a related field. A Master's or PhD degree is preferred.
Experience:
3+ years of experience in data architecture or a data architectural role within the aerospace or related high-tech industries.
Proven track record of contributing to data architectural initiatives and making data-related decisions that support evolving business needs.
Experience with data architecture frameworks and methodologies.
5+ years of experience designing and implementing scalable, distributed data systems.
3+ years of experience with big data technologies such as Hadoop, Spark, or similar platforms.
Strong expertise in data modeling, data warehousing, ETL processes, and real-time data processing.
Technical Skills:
Proficiency in data modeling tools (e.g., ER/Studio, PowerDesigner) and database systems (e.g., SQL Server, Oracle, NoSQL databases).
Advanced knowledge of cloud data services, including AWS (e.g., Redshift, RDS, S3) and data orchestration tools.
Solid understanding of data security best practices and regulatory compliance standards.
Leadership: Demonstrated ability to lead and mentor data architecture teams, fostering a collaborative and innovative environment.
Communication: Excellent ability to communicate complex data concepts to both technical and non-technical stakeholders, including executive leadership.
Must be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Nice To Haves

Advanced Degree: Master's degree in Computer Science, Data Science, Aerospace Engineering, Mechanical Engineering, or a related field.
Industry Expertise: Experience in the Manufacturing and/or Aerospace industry, with a strong understanding of industry-specific data challenges and solutions.
Data Analytics and BI: Proficiency in business intelligence and data analytics tools such as Tableau, Power BI, or similar platforms.
Certifications: Additional certifications in data architecture, data management, cloud data services, or related areas.
Strategic Planning: Experience in developing and executing data architectural roadmaps and strategies.
Innovative Projects: Involvement in high-impact, innovative data projects that have significantly advanced organizational goals.
Publications and Thought Leadership: Contributions to industry publications, conferences, or recognized thought leadership in data architecture and aerospace systems.

Responsibilities

Strategic Implementation: Assist in the development and execution of the data architecture strategy for Engines, ensuring alignment with Blue Origin's long-term vision and business objectives.
Architectural Design: Contribute to the design and implementation of complex, data-intensive systems across multiple programs, ensuring architectural integrity and compliance with industry standards.
Data Governance and Compliance: Support the establishment and enforcement of data governance frameworks, ensuring all data solutions adhere to regulatory requirements and Blue Origin's safety standards.
Innovation and Best Practices: Promote the adoption of advanced data technologies and methodologies, fostering a culture of continuous improvement and technical excellence within the data architecture teams.
Data Strategy Development: Assist in developing comprehensive data strategies that support business objectives, including data integration, storage, processing, and analytics.
Proof of Concept (PoC) Data Engineering:
Support PoCs: Participate in proof of concept projects to evaluate new data technologies, tools, and methodologies, demonstrating their feasibility and potential impact on Blue Origin's operations.
Evaluate Technologies: Help assess emerging data engineering technologies and frameworks, determining their applicability and benefits for existing and future projects.
Collaborate with Stakeholders: Work with stakeholders to define PoC objectives, requirements, and success criteria, ensuring alignment with business goals.
Document Findings: Assist in compiling reports and presentations on PoC outcomes, providing actionable insights and recommendations for full-scale implementation.
Cross-Functional Collaboration: Partner with stakeholders, including executives and department heads, to identify business challenges and develop comprehensive data architectural solutions that address these challenges.
Data Quality and Management: Ensure high standards of data quality, integrity, and security across all data systems, implementing robust data management practices.
Data Engineering Responsibilities:
Data Engineering Projects: Support and contribute to complex data engineering projects, ensuring they meet business requirements, timelines, and quality standards.
Improve Data Pipelines: Assist in designing and optimizing scalable, reliable, and efficient data pipelines to support real-time and batch data processing needs.
Mentor Data Engineers: Provide guidance and technical support to junior and mid-level data engineers, fostering professional growth and enhancing team capabilities.
Optimize Data Infrastructure: Help evaluate and improve data infrastructure, leveraging best practices to enhance performance, scalability, and cost-effectiveness.
Collaborate with Data Scientists: Work with data scientists to ensure data availability, accessibility, and quality for advanced analytics and machine learning initiatives.
Mentorship and Development: Mentor and support a team of data architects and engineers, providing guidance, knowledge sharing, and professional development to cultivate a high-performing data architecture function.
Resource Management: Assist in allocating and managing data architectural resources effectively, balancing project demands with team capabilities to achieve optimal outcomes.
Stakeholder Communication: Communicate data architectural concepts and strategies to a variety of audiences, including executive leadership, ensuring clear understanding and support for data initiatives.
Performance Optimization: Continuously evaluate and enhance the performance, scalability, and security of existing data systems, driving efficiencies across flight operations and engineering functions.

Benefits

Medical, dental, vision, basic and supplemental life insurance, paid parental leave, short and long-term disability, 401(k) with a company match of up to 5%, and an Education Support Program.
Paid Time Off: Up to four (4) weeks per year based on weekly scheduled hours, and up to 14 company-paid holidays.

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