Data Automation Engineer/Analyst - Level 2 or 3 (AHT)

The Central Region Systems Engineering organization within Northrop Grumman Space Systems pushes the boundaries of innovation, redefines engineering capabilities, and drives advances in various sciences. Our team is chartered with providing the skills and innovative technologies to develop, design, produce, and sustain optimized product lines across the sector while providing a decisive advantage to the warfighter. Come be a part of our mission as a Data Automation Engineer/Analyst (Level 2 or 3) in Aurora, CO.

Roles and Responsibilities:

• Develop, enhance, and maintain Python-based scripts, tools, and small applications that support data analysts and engineers on the New Moon program.

• Design and implement data processing pipelines using Python (e.g., NumPy, pandas, plotting libraries) for ingesting, cleaning, transforming, and analyzing large or complex datasets.

• Perform basic exploratory data analysis (EDA) to understand data quality, structure, trends, and anomalies, and communicate key findings to technical stakeholders.

• Apply working knowledge of statistics (distributions, hypothesis testing, regression, confidence intervals) to support data-driven decision-making and automation logic.

• Partner closely with data analysts and data scientists to understand their workflows, pain points, and analytical requirements, then translate those needs into robust, automatable tools and processes.

• Break down vague or high-level analyst requests into concrete technical tasks and deliver incremental improvements that add immediate value while building toward longer-term solutions.

• Use version control (Git) and collaborative development practices (branching, pull requests, code reviews) to ensure code quality, maintainability, and traceability.

• Debug and resolve issues that span data, configuration, and code across complex processing environments, including edge cases and unexpected data conditions.

• Create clear technical documentation and usage guides for internal tools, pipelines, and scripts to enable adoption and long-term maintainability.

• Participate in Agile ceremonies (e.g., sprint planning, stand-ups, retrospectives), contribute to backlog refinement, and collaborate effectively with cross-functional teams (systems engineering, software, data analysis, test).

• Communicate data-driven conclusions, trade-offs, and technical recommendations clearly to technical stakeholders and team leads.

Basic Qualifications:

Level 2:

• Bachelor’s degree in a science, technology, engineering, or mathematics (STEM) discipline and 2+ years of relevant experience; 0+ years with a Master’s degree; or an additional 4 years of relevant experience may be considered in lieu of a degree.

• Must have active TS Clearance with SCI eligibility at time of application.

• Proficiency in Python for scripting, automation, and data processing, including experience with common data and scientific libraries (e.g., NumPy, pandas, plotting libraries such as Matplotlib, Seaborn, or Plotly).

• Experience developing and maintaining internal tools, scripts, or small applications used by data analysts or other engineers.

• Experience working with large or complex datasets and performing basic exploratory data analysis (EDA).

• Familiarity with version control and collaborative development practices (e.g., Git, branching strategies, code reviews).

Level 3:

• Bachelor’s degree in a science, technology, engineering, or mathematics (STEM) discipline and 5+ years of relevant experience; 3+ years with a Master’s degree; or an additional 4 years of relevant experience may be considered in lieu of a degree.

• Must have active TS Clearance with SCI eligibility at time of application.

• Proficiency in Python for scripting, automation, and data processing, including experience with common data and scientific libraries (e.g., NumPy, pandas, plotting libraries such as Matplotlib, Seaborn, or Plotly).

• Experience developing and maintaining internal tools, scripts, or small applications used by data analysts or other engineers.

• Experience working with large or complex datasets and performing basic exploratory data analysis (EDA).

• Working knowledge of statistics for data analysis (e.g., distributions, hypothesis tests, regression, confidence intervals).

• Demonstrated ability to draw clear, data-driven conclusions and communicate them to technical stakeholders.

• Familiarity with version control and collaborative development practices (e.g., Git, branching strategies, code reviews).

• Experience working closely with data analysts and/or data scientists to understand analytical workflows and translate them into scalable, maintainable tools and pipelines.

• Proven ability to break down vague or evolving analyst requests into clear technical requirements, prioritize work, and deliver incremental improvements in an Agile environment.

• Demonstrated ability to independently investigate and resolve complex issues that span data, configuration, and code in intricate processing environments.

• Experience supporting data-intensive or mission-focused programs in the defense, aerospace, or national security domain.

• Experience integrating automated data processing or analytics pipelines into CI/CD workflows.

• Experience with dashboarding or reporting tools (e.g., custom web dashboards, BI tools) to expose data and metrics to stakeholders.

• Familiarity with cloud or high-performance computing environments and their data processing patterns.