The Data Engineer will be writing code that moves data through a pipeline, fixing data pipeline issues, optimizing data systems, and collaborating with stakeholders, day to day.
The Capital Software Project is building a data fabric system. The data fabric system includes a data pipeline that will be moving complex mix of data types and formats to a data lake and a series of databases. Allowing mission engineering analyst to conduct data analysis from authoritative sources of truth.
The Data Engineer will be working with the Systems Engineering and DevSecOps teams to ensure that datasets are properly converted, transformed, routed and stored. Create ETL/ELT code to ingest, transform, and load data from a variety of sources into the data lake and scale. Primary data sources will be mission engineering data and physics-based simulation results.
How you will contribute to our National Security and Defense mission:
As a Data Engineer will be working with the Systems Engineering and DevSecOps teams to ensure that datasets are properly converted, transformed, routed and stored, as designed. You will also bring your experience in harvesting metadata from datasets. You’ll bring your experience in multi-source and cross-domain data integration.
Day-to-day, you will be blending your software engineering, data architecture, and operational monitoring skills to:
Build And Maintain Data Pipelines To
- Write or update ETL/ELT code that ingests data from APIs, databases, or files.
- Implement transformations to clean, standardize, or enrich data.
- Optimize pipeline performance and improve reliability.
- Hands-on experience with AI and ML pipelines, MLOps workflows, and data processing methodologies.
- Implement methods for data traceability and lineage.
Monitor Pipelines And Data Quality To
- Check automated alerts and logs for failed jobs or data anomalies.
- Troubleshoot issues such as schema changes, missing data, or performance bottlenecks.
- Validate data accuracy and consistency across systems. Leverage your expertise in semantic modeling
Collaborate With Engineering Teams To
- Meet with project teams to understand new data requirements.
- Work with backend engineers or DevSecOps to align pipeline changes with system updates.
- Support stakeholders by providing data extracts or explanations of data structure.
Design and Improve Data Architecture
- Plan new data models or schemas for analytics or application use case.
- Incorporate metadata strategies tailored fit for the use case.
- Help shape the data warehouse/lake structure.
- Evaluate new tools or cloud services to improve scalability and maintainability.
Write Code and Documentation
- Build reusable application containers in Python, SQL, or other languages used in the stack.
- Document pipeline logic, data contracts, and system diagrams.
- Participate in code reviews to ensure quality and best practices.
Work Location:
Due to the security classification for this project, work will be performed in-office, 5-days a week.
You’ll be a great fit for this role if: (SOFT SKILLS)
- You have a passion for technology.
- You bring a forward-looking mindset, anticipating needs and designing scalable, future-ready data structures.
- You approach complexity with innovation and drive, identify and resolve challenges quickly.
- You rigorously deliver high-quality, actionable solutions that enhance mission execution.
- You understand the Department of Defense reference and compliance architectures.
- You are passionate about continuous learning and growth, and seek opportunities to challenge yourself.
- You have excellent communication skills.
Responsibilities
Your job functions will include but may not be limited to:
- Develop and maintain ETL/ELT pipelines to ingest, transform, and load data from a variety of sources into our data warehouse or data lake.
- Design scalable and reliable data architectures, including schemas, workflows, and integration layers.
- Optimize data models, ensuring alignment with analytics and operational needs.
- Collaborate cross-functionally to understand data requirements and provide technical solutions.
- Monitor pipeline performance, troubleshoot data issues, and implement continuous improvements.
- Ensure data quality, integrity, and security throughout the entire data lifecycle.
- Automate data workflows using scripting, orchestration tools, and CI/CD practices.
- Maintain documentation related to data processes, standards, and best practices.
- Design scalable and reliable data architectures, including schemas, workflows, and integration layers.
- Conduct design reviews, validate solution architectures, and ensure alignment with enterprise standards.
- Bring Solid understanding of DoD frameworks, security requirements, and best practices for classified and unclassified environments.
Qualifications Required
- 7+ years of relative working experience as a Senior Data Engineer or in a related field.
Strong experience with ETL/ELT development and building data pipelines.
Proficiency with at least one major programming language (e.g., Python, Java, Scala).
- Experience working with SQL and relational databases (e.g., PostgreSQL, SQL Server, MySQL).
- Exposure and familiarity with data services on modern cloud platforms (AWS, Azure, GCP, etc.).
- Familiarity with modern data warehousing technologies (e.g., ADLS, Redshift, BigQuery, Synapse).
Education
- Bachelor’s degree Computer Science, Software Engineering, or a related field.
Clearance Requirements
- Must have a Secret DoD Security Clearance.
- Must be a US Citizen.
The pay range for this position is $140,000/year to $190,000/year; however, base pay offered may vary depending on established government contract ranges, job-related knowledge, skills, and experience, and other factors. MTSI offers a full range of medical benefits, 401k, ESOP, paid time off, and other benefits, dependent on the position offered. Base pay information is based on market location. Applications will be accepted on an ongoing basis. This posting will be renewed periodically until the position is filled.
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