Data Engineer - MLOps

Data Engineer 2 - MLOps

Pacific Northwest National Laboratory (PNNL) invites applications for a Data Engineer 2 – MLOps. PNNL is a world‑class research institution focused on National Security, Earth & Biological Sciences, Physical & Computational Sciences, and Energy & Environment. The Data Engineer will work in the AI and Data Analytics Division (AIDA) of the National Security Directorate, developing scalable data architectures, pipelines, and AI/ML solutions that support complex mission challenges.

At PNNL, core capabilities are organized into directorates, each with dedicated leadership and budget. These include National Security;
Earth & Biological Sciences;
Physical & Computational Sciences; and Energy & Environment. AIDA, part of the National Security Directorate, combines domain expertise with advanced hardware and software to deliver computational solutions across the data analytics lifecycle—from acquisition and management to analysis and decision support.

• Identify mission challenges and methodically formulate engineering solutions.
• Demonstrate software engineering excellence and deliver high‑quality results at scale.
• Develop software using a high‑level programming language such as Python.
• Apply strong design principles and innovative problem‑solving skills to complex technical challenges.
• Stay current on advancements in data management and database technologies.
• Take initiative in setting and pursuing personal goals and professional growth.
• Mentor and support the development of junior scientists and engineers.
• Communicate effectively, both verbally and in writing, and collaborate successfully in a team environment.

• Mission‑Critical Development:
  • Design, develop, test, and deploy software applications that directly contribute to the nation’s mission objectives.
  • Collaborate with Government and Industry partners to understand mission needs, translate requirements into scalable software solutions.
• Innovative Problem Solving:
  • Tackle complex technical challenges with creativity and innovation.
  • Propose and implement solutions that go beyond conventional approaches, ensuring efficient and impactful software.
• End‑to‑End Ownership:
  • Take ownership of the entire software development lifecycle, from concept to deployment.
  • Ensure reliability, security, and performance of mission‑critical software systems.
• Collaborative Teamwork:
  • Work in an agile environment with multidisciplinary teams, including software engineers, cloud engineers, machine learning engineers, data scientists, UX/UI designers, front–end developers, scrum masters, product owners, and users.
  • Participate in code reviews and knowledge‑sharing sessions to enhance overall team skill set.
• Continuous Learning:
  • Stay up‑to‑date with industry trends and emerging technologies to bring innovative ideas.
  • Actively participate in training and development opportunities to enhance your skills and contribute to team growth.
  • Have opportunities to attend conferences and engage in industry events.

• Programming & Scripting:
  Python, C#/.NET, Bash, Power Shell, JavaScript, Type Script, Java, C/C++.
• Platforms: AWS, Azure, On‑Prem, IoT/ICS, GCP.
• Development/Lifecycle:
  Agile/Scrum/Kanban, Gitlab/Atlassian, CI/CD & Dev Sec Ops .
• Paradigms:
  Rapid prototypes with CSP managed services, well‑architected solutions using Infrastructure as Code, compliant deployments in highly‑regulated environments.
• Data & Storage: S3, Athena, Postgre
  
  SQL, Elasticsearch/Open Search, Dynamo
  
  DB, Redshift, Mongo
  
  DB, Data Bricks, Apache Spark.

• Volume – large, terabytes and petabytes of data.
• Variety – images, audio, text, IoT, RF, GPS, edge sensors.
• Velocity – sub‑second and lower frequency.

• Detect and prevent smuggling of drugs and contraband at ports of entry.
• Develop large data pipelines to thwart funding for terrorists, nuclear proliferators, drug cartels, and rogue leaders.
• Apply big data solutions to national security problems.
• Develop capabilities for scalable geospatial analytics.
• Use remotely sensed imagery to identify and monitor wildfire progression.
• Analyze resiliency of the electric power grid to prevent…