Aerstone Data Engineer Springfield, VA · Full time Company website

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Aerstone is proud to be a service-disabled, veteran-owned small business (SDVOSB) certified by the National Veteran Business Development Council (NVBDC) and the US Small Business Administration. With two decades of service, we have earned accreditation from the National Security Agency (NSA) as a Certified Vulnerability Assessor, providing highest-level cybersecurity expertise to federal government, military, and intelligence agencies, as well as a wide range of private industries. Our clientele spans the commercial and federal sectors, including financial services, legal, utilities, education, and non-profit organizations. We provide unparalleled support and cleared staff to federal organizations in the civilian, military, and intelligence communities. Our suite of services covers every facet of cybersecurity, encompassing architecture, systems design, software development, training, standards-based assessment, and penetration testing.

About Aerstone

Aerstone is a cybersecurity and software development firm delivering secure, scalable, and mission-critical technology solutions for government and commercial partners. We specialize in building trustworthy systems that support complex regulatory environments and high-stakes missions. Our teams operate with a high degree of autonomy, technical rigor, and accountability—focused on outcomes that matter.

At Aerstone, you’ll work alongside experienced engineers and security professionals in a collaborative, mission-driven environment where your expertise directly impacts national security objectives.

Position Overview:

We are seeking a skilled and motivated Data Engineer / Database Engineer to support our growing team providing an enterprise data warehouse and visualization environment. The ideal candidate will have hands-on experience with Microsoft SQL Server, ETL pipelines, and cloud-based data ingestion tools—especially AWS Glue. You will be responsible for maintaining and enhancing our database systems, enabling near real-time data pipelines from source databases (Oracle, SQL, etc) to Microsoft SQL Server, and ensuring secure, efficient, and scalable data access.

Key Responsibilities:

• Support and maintain Microsoft SQL Server environments, with flexibility to adapt to alternative database platforms as the architecture evolves.
• Design and implement data pipelines using AWS Glue for efficient and scalable data ingestion.
• Build and maintain a near real-time data ingestion framework from Oracle databases to Microsoft SQL Server.
• Develop and manage ETL processes, including incremental/delta-based extraction of raw data from source systems.
• Build and optimize relational database schemas, ensuring performance, scalability, and data integrity.
• Implement and manage fine-grained roles and permissions in SQL Server to enforce data security and access control policies.
• Work closely with Data Analysts, Software Engineers, and other stakeholders to ensure data systems meet business requirements.
• Monitor and troubleshoot data pipelines and workflows to ensure reliability and consistency.

Qualifications:

• Proven experience with Microsoft SQL Server administration and development.
• Proficiency in ETL/ELT concepts and experience with tools like AWS Glue, Apache Spark, or equivalent.
• Solid understanding of Oracle database systems and data extraction methodologies (especially delta/change data capture techniques).
• Experience with cloud data platforms, particularly AWS (S3, Glue, RDS, etc.).
• Strong SQL skills and experience with role-based access control in database systems.
• Familiarity with scripting or programming languages (e.g., Python, Shell) for automation and data processing.
• Ability to work independently and communicate effectively in a collaborative team environment.

Preferred Skills (Not Required):

• Proficiency with Oracle GoldenGate or equivalent CDC (Change Data Capture) tools for real-time replication.
• Experience with modern data architectures (e.g., Data Vault 2.0).
• Knowledge of CI/CD practices for data engineering.
• Exposure to data cataloging and metadata management tools.