Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Data Engineer
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, build, and maintain scalable ETL/ELT data pipelines
Develop and maintain real-time data streaming solutions (Kafka, Flink, Spark Streaming)
Optimize and automate data workflows as data volumes grow
Oversee data model and schema design for analytics and reporting
Mentor and guide junior data engineers
From the employer’s posting
Design, build, and maintain highly scalable, reliable, and efficient data pipelines
Develop, deploy, and maintain real-time data streaming solutions
Optimize and automate data workflows, ensuring that data pipelines are efficient
Oversee the development of data models and schema designs
Mentor and guide junior data engineers
What you’ll bring
All qualificationsCore experience
- 5+ years in data or software engineering with complex pipelines
- Bachelor's degree in computer science, information systems, or related field (or equivalent experience)
- Top Secret/SCI clearance required
- Strong understanding of data validation and performance evaluation
- Excellent technical communication with non-technical audiences
Preferred experience
- 4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
- Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark).
- Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
- Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
Qualification wording
5+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines
Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field
Clearance Level: Top Secret/SCI required
Strong understanding of data validation, model testing, and performance evaluation techniques.
Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.
4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark).
Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
Education & alternatives
Education and Background - Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (masters degree preferred)., and 5+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines., or equivalent relevant work experience; e.g., each year of work experience may be substituted for each year of education required. Years of Experience
About Agile-Defense
At Agile Defense we know that action defines the outcome and new challenges require new solutions.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 23, 202612 days ago
- Recorded sightings
- 25
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 12
Similar jobs usually come down between day 6 and day 54.
From 10,764 similar postings that came down. Coming down is not always a hire.
Agile-Defense is hiring
29 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Databricks
- Kafka
- MLflow
- Spark
- Tableau
- Plotly
- PySpark
- scikit-learn
- TensorFlow
- XGBoost
- Matplotlib
Where the posting names them
- 4+ years of experience in applied data science, machine learning engineering, or data pipeline development. - Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark). - Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
- Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow). - Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry). Working Conditions
- Design, build, and maintain highly scalable, reliable, and efficient data pipelines for extracting, transforming, and loading (ETL/ELT) data from various sources into data warehouses, data lakes, and other storage systems. - Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure the efficient flow of data across various platforms and systems. Develop, deploy, and maintain real-time data streaming solutions to process and deliver data with low latency (using tools like Apache Kafka, Flink, or Spark Streaming). - Optimize and automate data workflows, ensuring that data pipelines are efficient, reliable, and capable of handling increasing data volumes.
- Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark). - Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow). - Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
- Strong understanding of data validation, model testing, and performance evaluation techniques. - Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib. - Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Applying through Lever
- No account needed: one form, and Lever reads your resume into the profile recruiters search.
Already applied? Track this application
Has Agile-Defense posted this job before?
Yes. We’ve followed 2 other Data Engineer jobs there since March 2026. One came down after 132 days. One is still up.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
About Agile Defense
At Agile Defense we know that action defines the outcome and new challenges require new solutions. That’s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.
Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility—leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation’s vital interests.
Requisition #: 1956
Job Title: Data Engineer
Location: Omaha, NE
Clearance Level: Top Secret/SCI required
Job Description
- Design, build, and maintain highly scalable, reliable, and efficient data pipelines for extracting, transforming, and loading (ETL/ELT) data from various sources into data warehouses, data lakes, and other storage systems.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure the efficient flow of data across various platforms and systems. Develop, deploy, and maintain real-time data streaming solutions to process and deliver data with low latency (using tools like Apache Kafka, Flink, or Spark Streaming).
- Optimize and automate data workflows, ensuring that data pipelines are efficient, reliable, and capable of handling increasing data volumes.
- Oversee the development of data models and schema designs to ensure accurate, accessible, and high-performance data storage for analytics and reporting.
- Ensure data quality, integrity, and consistency by implementing data validation, monitoring, and error-handling mechanisms.
- Monitor and troubleshoot performance bottlenecks in data systems, resolving issues with data processing and data access.
- Stay current with emerging trends and best practices in data engineering, recommending new tools, technologies, and methods to enhance existing infrastructure.
- Mentor and guide junior data engineers, promoting best practices in data engineering and fostering a collaborative, high-performance team environment.
Education and Background
- Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (masters degree preferred)., and 5+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines., or equivalent relevant work experience; e.g., each year of work experience may be substituted for each year of education required.
Years of Experience
5+ years
Required Skills
- Strong understanding of data validation, model testing, and performance evaluation techniques.
- Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib.
- Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.
Preferred Skills
- 4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
- Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark).
- Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
- Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
Working Conditions
Onsite in a SCIF in STRATCOM
Our Core Values
Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together.
What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are.
- Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do.
- Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated.
- Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support.
- Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task.
- Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges.
- Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
Employment type
Regular
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Omaha, NE
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.