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# Data Engineer - Mid-Level

- **Company:** BAE Systems
- **Location:** Rockville, MD, United States
- **Experience:** Experienced
- **Salary:** $97,008.0 - $164,914.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, BigQuery, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Mining, Data Systems, Data Warehousing, Query Languages, Apache Hadoop, Monitoring of Systems, JSON, Python (Programming Language), Machine Learning, NumPy, Data Streaming, Extensible Markup Language (XML), Jupyter Notebook, Data Processing, Feature Engineering, Snowflake, Apache Spark, Pandas, Matplotlib, Information Technology, Data Analytics, Apache Kafka, Feature Selection, Data Pipelines, Amazon Redshift
- **Published:** October 13, 2026
- **Apply:** https://jobs.baesystems.com/global/en/job/131440BR

## About the Role

Required Education, Experience, & Skills Typical education and years of related/relevant experience required: Bachelor's Degree and minimum of 4 years of proven experience supporting DoD programs or large-scale weapon systems; or Master's Degree and minimum of 2 years of relevant experience.
Preferred Education, Experience, & Skills

 * Bachelor's degree or higher in Computer Science, Data Engineering, or a related STEM field
 * 4+ years of experience in data engineering or a similar role
 * Strong understanding of the Data Engineering process
 * Proficiency with data modeling notations
 * Proficiency in data manipulation libraries (e.g., NumPy, Pandas, Matplotlib, Seaborn)
 * Proficiency in programming languages (e.g., Python, JSON/XML, structured and unstructured query languages, and Jupyter Notebooks)
 * Experience with ETL/TS tools and frameworks
 * Experience with data analytics, data mining, and statistical analysis
 * Experience with data warehousing solutions and technologies, including RedShift, BigQuery, and Snowflake
 * Familiarity with big data technologies like Hadoop, Spark, and Kafka
 * Excellent problem-solving and collaboration skills

## Description

This position is both an internal and customer facing position and responsible for supporting the roll out and implementation of a new data engineering solutions to support Navy functions. In this role, you will plan and coordinate the preparation of project documentation, such as business process maps, training, job aids, schedules, and presentations, to ensure the data engineering solutions meet internal BAE Systems and customer requirements. You will engage with Navy customers and coordinate with the internal BAE Systems technical team to design, implement, and tailor the developed solutions that may be based on COTS or GOTS technology. In this position, you will perform data engineering, data pipeline building, business process mapping, technical analysis, trade studies, research, development, and test and evaluation to enable quality management and business process system implementation. You will help resolve issues and make recommendations regarding enhanced capabilities for the
proposed COTS / GOTS data engineering solutions. You will analyze proposed changes of product design to determine effect on overall product and system and coordinate modification for management control., * Deliver data engineering Design and implement scalable data pipelines that support AI/ML applications, leveraging techniques such as data warehousing, ETL (Extract, Transform, Load), and data streaming.

 * Perform data wrangling, merging, cleaning, normalization, and transformation to prepare data for analysis
 * Conduct feature engineering and feature selection to optimize data for AI/ML model development
 * Work closely with Data Solution Architects and AI/ML Developers to prepare data for analytics and modeling tasks
 * Implement data pipelines enabling retrieval of data from federated data systems
 * Implement monitoring systems to ensure data pipeline reliability and performance
 * Implement algorithms required to perform data engineering functions
 * Implement data quality checks and monitoring processes
 * Stay updated on best practices and emerging technologies in data engineering