Key Responsibilities
- Gain exposure to how large companies manage data across different areas like engineering, supply chain, finance, and manufacturing.
- Learn how data is used to support decision‑making, dashboards, operations and reporting.
- Assist with simple data quality checks or structured cleanup tasks under mentor guidance.
- Work with senior IT leaders to understand high‑level data challenges and turn them into small, hands‑on prototype opportunities.
- Collaborate on innovation initiatives that use modern data engineering, cloud capabilities, and predictive analytics to generate measurable business impact.
- Learn how different systems (like SAP, cloud platforms, or analytics tools) connect/share data.
- Learn what “data governance” means and why accuracy, consistency, and security matter in large organizations.
- Help with documentation related to data definitions, business rules, or how a prototype handles data.
- Learn foundational concepts about data security, classification, and why certain industries follow strict rules.
- Follow security guidelines while working with data in prototypes or testing environments.
- Gain early exposure to enterprise systems like SAP and cloud platforms so you can grow into more advanced data roles in the future.
- Participate in learning sessions with senior leaders to understand how enterprise data supports major programs.
YOU MUST HAVE
- Bachelor’s degree (completed or in final year) in Computer Science, Data Science, IT, Engineering, or related technology discipline.
- Ability to write code in at least one language (Python, SQL, Java, JavaScript/TypeScript).
- Understanding of fundamental computer science concepts: algorithms, data structures, databases, debugging, and SDLC basics.
- Exposure to at least one relevant area: web development, scripting/automation, cloud platforms, AI/ML, data analytics, or enterprise applications.
- Strong problem‑solving skills, curiosity, willingness to learn fast, and ability to communicate.
- Ability to work effectively with mentors, peers, and cross‑functional stakeholders.
WE VALUE
- Hands‑on experience through academic projects, internships, capstones, or hackathons.
- Exposure to Python data libraries, data cleaning, automation scripts, or analytics notebooks.
- Experience with dashboards or BI tools (Power BI, Tableau, SAP Analytics Cloud).
- Familiarity with cloud concepts (AWS/Azure fundamentals, APIs, IAM, serverless functions).
- Exposure to AI/GenAI concepts (prompt engineering, embeddings, model evaluation, RAG).
- Experience using Git, GitHub, Copilot, VS Code, CI/CD basics, or Agile tools such as JIRA.
Technical Skills
Programming & Scripting
- Basic Python skills for data analysis or simple automation
- SQL fundamentals for querying and working with data
- Optional exposure to Java or JavaScript
- Optional basic scripting experience (PowerShell or Bash)
Data & Analytics
- Understanding of how to clean, organize, and prepare data
- Ability to build simple dashboards using tools like Power BI or Tableau
- Exposure to basic analytics or introductory machine learning concepts
Cloud & Data Platforms
- General awareness of cloud platforms (AWS, Azure, Snowflake)
- Understanding of APIs at a beginner level
- Basic knowledge of how data moves between systems
Tools & Productivity
- Experience using Git or GitHub for version control
- Familiarity with IDEs like VS Code
- Exposure to work‑tracking tools (such as JIRA)
- Basic troubleshooting skills (debugging simple code or data issues)
Skills Required
- Bachelor's degree completed or in final year in Computer Science, Data Science, IT, Engineering, or a related technology discipline
- Ability to write code in at least one language: Python, SQL, Java, or JavaScript/TypeScript
- Fundamental knowledge of algorithms, data structures, databases, debugging, and software development lifecycle basics
- Exposure to at least one area including web development, scripting/automation, cloud platforms, AI/machine learning, data analytics, or enterprise applications
- Strong problem-solving skills, curiosity, willingness to learn quickly, and communication ability
- Ability to work effectively with mentors, peers, and cross-functional stakeholders
- Hands-on experience through academic projects, internships, capstones, or hackathons
- Exposure to Python data libraries, data cleaning, automation scripts, or analytics notebooks
- Experience with dashboards or business intelligence tools such as Power BI, Tableau, or SAP Analytics Cloud
- Familiarity with AWS or Azure fundamentals, APIs, IAM, or serverless functions
- Exposure to AI or generative AI concepts such as prompt engineering, embeddings, model evaluation, or RAG
- Experience with Git, GitHub, Copilot, Visual Studio Code, CI/CD basics, or Agile tools such as JIRA
- Basic Python skills for data analysis or simple automation
- SQL fundamentals for querying and working with data
- Understanding of data cleaning, organization, and preparation
- Ability to build simple dashboards using Power BI or Tableau
- Exposure to basic analytics or introductory machine learning concepts
- General awareness of AWS, Azure, or Snowflake
- Beginner-level understanding of APIs and data movement between systems
- Basic troubleshooting and debugging skills for code or data issues
The Aerospace Corporation Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Aerospace Corporation and has not been reviewed or approved by The Aerospace Corporation.
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Retirement Support — The 401(k) plan provides a company‑paid contribution of 8–12% based on years of service with immediate eligibility and vesting, and eligible employees can access retiree medical benefits.
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Leave & Time Off Breadth — Paid time off includes 15 vacation days (rising to 20 after five years), nine paid holidays, and unlimited sick time for exempt employees with accruals for non‑exempt staff.
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Flexible Benefits — Flexible work models include a 9/80 schedule with alternating Fridays off, supported by backup care services, an EAP, relocation assistance, and home‑office stipends where applicable.
The Aerospace Corporation Insights
What We Do
The space enterprise has been transformed by rapid change and growth. New vehicles for national security space, a more rapid launch cadence, proliferated satellite constellations, the pursuit of interplanetary exploration, and thriving commercial ventures are changing the nature of the space industry. The Aerospace Corporation (Aerospace) is a leading architect for U.S. space programs, shaping efforts to outpace threats to our national security while cultivating the technologies needed to further this new era of space commercialization and exploration. Aerospace works across the space enterprise in service of the public interest. In addition to supporting the Department of Defense and the Intelligence Community, our customers include NASA, NOAA, numerous federal agencies, and commercial space — all of whom benefit from our deep technical knowledge. We only pursue business related to the space mission and complementary fields, operating as the nation’s trusted partner to solve the toughest challenges and develop reliable and innovative technologies. Innovation in space occurs when people have the freedom to imagine and do. At Aerospace, we take pride in our readiness to solve some of the most complex challenges in the space enterprise.
Why Work With Us
We are a non-profit corporation chartered by the government to work on the hardest problems in space. We employ technical experts in every discipline of space-related science and engineering who touch every part of the US space program. Come join us as we make an impact bigger than ourselves.
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