Chief Data Engineer

Responsibilities

We are in search of a forward-thinking Chief Data Engineer to lead our data engineering initiatives focused on designing and architecting scalable data infrastructure and systems. This essential leadership role is charged with crafting and executing a data strategy that supports Noblis’ Vision 2030 strategic objectives, especially in the context of enterprise scaling and data-driven initiatives.  The ideal candidate will bring an applied technical background in data engineering and architecture, with a significant track record in pioneering data-driven solutions that bolster efficiency, innovation, scalability, and compliance within complex regulatory environments.

Key Responsibilities:

• Collaborate closely with the CEO, CTO, CIO/DCIO and Mission Area Vice Presidents to define and prioritize data and analytics needs, particularly in support of corporate knowledge management and enterprise scaling initiatives, Noblis Sponsored Research, and a wide range of platforms with massive performance needs for computing such as AI/ML and immersive technology/XR platforms.
• Collaborate with CIO/DCIO to develop and execute the organization’s data strategy, ensuring it aligns with business goals and adheres to strict government contracting regulations.
• Design, build, and maintain scalable and resilient data management systems, data lakehouse initiatives, and data architectures capable of supporting the organization’s growth and technological advancements.
• Serve as a senior technical advisor for client-facing and research initiatives for scaling distributed and open data architectures.
• Oversee the selection and integration of advanced data technologies and tools, including AI/ML algorithms and XR platforms, to keep the organization at the forefront of technological innovation.
• Architect the organization’s data infrastructure to ensure scalability, efficiency, and alignment with business, regulatory requirements and future client-focused solutions and services.
• Establish robust data governance and quality control frameworks to guarantee data security, data accuracy and accessibility.
• Promote the organization’s capabilities in leveraging advanced technologies, including AI/ML and immersive technologies in client-facing and internal initiatives.
• Work across diverse scientific and technical disciplines to translate technical architectures into proposal solutions.
• Ensure compliance with all relevant government contracting regulations, emphasizing data security and integrity.
• Maintain awareness of industry trends and technological advancements, leveraging insights to drive organizational improvement and competitive advantage.
• Guide, mentor, and provide leadership with data engineers, cultivating an environment of innovation, high performance, diverse thought and continuous learning.

**This position is located in Reston, VA with the ability to work in a hybrid work environment.

Required Qualifications

• Master’s degree in computer science, Data Science, Information Systems, Engineering, or a related field.
• High profile technical experience as a Chief Engineer or related technology-forward executive position with demonstrated experience interfacing frequently with clients, partners, and employees.
• Must have 15+ years of experience in data engineering or a related field, with at least 10 years in a hands-on leadership role. Exceptional leadership skills and experience managing and/or collaborating across multiple technical teams in high-stakes, fast-paced environments is required.
• Expert background in software engineering, database management, data architecture, networking, infrastructure design, and deployment.
• Proven expertise in commercial software pricing to define structures based on volume, capacity, and usage patterns such as database as a service (DBaaS), platform as a service (PaaS), infrastructure as a service (IaaS), and software as a service (SaaS).
• Proven expertise in data modeling, data lakehouse architectures, data warehousing, ETL processes, and big data technologies to include integrating data from multiple sources into a common information pool for use by data scientists and ML engineers across multiple disciplines.
• Expertise in containerization and data orchestration (e.g., Docker, Kubernetes, etc.)
• Expert proficiency working in both Linux and Windows operating environments with DevSecOps, automated software deployment and full-lifecycle CI/CD experience.
• Proficiency in designing architectures for relational database management systems (RDBMS) including PostGres, Oracle, MS SQL Server, and noSQL.
• Expert proficiency in programming languages such as Shell Scripting, C, C++, Python, SQL and/or PL/pgSQL, and Java, along w