← Search all jobs

Enterprise Architect - Data Engineer

Arcfield

McLean, VA · Posted November 3, 2026

Just laid off? Start here: a plan for the first weeks

See every open role at Arcfield

More in Virginia job market · All Enterprise Architect jobs (48) · Manufacturing & Industrial · Data & Analytics jobs

More roles at Arcfield

Similar jobs

Where McLean, VA ranks

Where McLean, VA placed in our monthly rankings, month by month. Each month stays online at its own address.

How AI is used in this kind of work

Among database architects, AI is already used for a large share of the tasks. Measured exposure for database architects: 58% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

Check how this applies to your own job

Skills this job asks for

Say which you have and which you want to build. We use it to match you to jobs like this one.

  • Python
  • AWS
  • Machine learning
  • Azure
  • Java

About the job

Responsibilities

Ready to make an impact on a mission that matters? Join Arcfield and be part of a team delivering innovative engineering and technology solutions that help advance our nation's security. At Arcfield , you'll have the opportunity to tackle meaningful challenges alongside talented, driven professionals who bring diverse skills, perspectives, and expertise to the mission. We're looking for motivated, curious, and adaptable individuals who thrive in dynamic environments, embrace new challenges, and are eager to learn, grow, and make a difference. Whether you're building on your existing expertise or ready to take the next step in your career, Arcfield offers an environment where you can expand your skills, explore new opportunities, and contribute to work that has a real impact.

The Data Engineer works on unusually complex technical problems, develops highly innovative solutions, and exercises considerable independence in determining the approaches necessary to achieve desired results. The Data Engineer shall support the Sponsor's mission by applying technical expertise to complex data challenges while collaborating with cross-functional teams.

Responsibilities include, but are not limited to , the following:

Designing and implementing scalable data architectures to support real-time data processing and integration, with a focus on enabling the mission while minimizing cost and complexity.

Collaborat ing with the Data Scientist to effectively deliver data streams of interest and prioritize certain data types for quick analysis.

Develop ing data pipelines to support data integration.

Develop ing and maintain ing data quality checks.

Engag ing with high-priority stakeholders to provide data-driven solutions.

Work ing with downstream data repositories to ensure needs are met and data flow is optimized .

Meet ing the needs of customers unfamiliar with the data or data engineering concepts, including targeters and engineers.

Develop ing data filtering and processing algorithms.

Establishing new data flows to integrate external data sources into Sponsor repositories using AWS methods and non-traditional options.

Ensur ing compliance with relevant data stewardship, documentation, and security r equirements.

Providing technical leadership and direction in implementing enterprise information/data management practices.

Leading and participating in information/data management projects, including the Enterprise Information Architecture, information models and flows, data dictionaries, data standards, and data quality processes and standards.

Developing and maintaining the logical Enterprise Information Architecture that enables seamless information interoperability among transaction systems, document management systems, and information delivery systems.

Qualifications

Must possess and be able to maintain a TS/SCI clearance with polygraph.

Bachelor's d egree (or equivalent experience) in the fields of Computer Science, Information Systems, Engineering, Business, or a related scientific or technical discipline.

BS 10-12, MS 8-10, PhD 5-7

Knowledg e of and experience with the Sponsor’s environment .

Experience with the following: Cloud-based data platforms like AWS, GCP, or Azure.

System architecture and implementation of data solutions.

Data engineering tools and techniques.

Programming languages such as Python, Java, or C++.

B uilding data pipelines and integrating multiple data sources .

W ork ing with challenging data sets and developing data filtering and processing algorithms .

Developing information architectures aligned with information lifecycle management.

Performing conceptual, logical, and physical data modeling using data modeling tools and database design techniques in complex, large-scale data environments.

Transactional data modeling, dimensional modeling, and object - oriented modeling.

Developing scalable entity designs using advanced data structures (e.g., tall tables).

Developing data models that support time dependencies, historical tracking, simple and complex taxonomies, and multilingual data.

Creating data dictionaries, defining metadata management approaches, and establishing governance processes.

Developing and implementing IT architecture plans, Enterprise Information Architecture standards and guidelines, software development methodologies, and strategic plans.

Developing data sharing standards and architecting scalable service - oriented solutions.

Creating enterprise models incorporating master and reference data.

Solid understanding of transaction and information systems, data warehouses, data marts, ODS, MDM methodologies and life cycles, as well as ETL and MDM technologies.

Knowledge of application modeling languages/techniques (e.g., UML, OML, entity relationship modeling, DFDs), including the ability to create and read the associated diagrams.

Desire d

Familiarity with data visualization tools such as Tableau or Power BI .

Experience with machine learning frameworks such as TensorFlow or PyTorch .

Experience with data quality management and data validation techniques .

Ability to work with sensitive data sources and develop data anonymization algorithms .

Equal Pay Act

This is the projected compensation range for this position. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, Arcfield invests in its employees beyond just compensation. Arcfield ’s benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, Short Term and Long-Term Disability, Retirement and Savings, Learning and Development opportunities, wellness programs as well as other optional benefit elections.

Min: $125,133.53 Max: $217,582.94 EEO Statement

We are an equal opportunity employer and federal government contractor. We do not discriminate against any employee or applicant for employment as protected by law.

Ready to make an impact on a mission that matters? Join Arcfield and be part of a team delivering innovative engineering and technology solutions that help advance our nation's security. At Arcfield , you'll have the opportunity to tackle meaningful challenges alongside talented, driven professionals who bring diverse skills, perspectives, and expertise to the mission. We're looking for motivated, curious, and adaptable individuals who thrive in dynamic environments, embrace new challenges, and are eager to learn, grow, and make a difference. Whether you're building on your existing expertise or ready to take the next step in your career, Arcfield offers an environment where you can expand your skills, explore new opportunities, and contribute to work that has a real impact.

The Data Engineer works on unusually complex technical problems, develops highly innovative solutions, and exercises considerable independence in determining the approaches necessary to achieve desired results. The Data Engineer shall support the Sponsor's mission by applying technical expertise to complex data challenges while collaborating with cross-functional teams.

Responsibilities include, but are not limited to , the following:

Designing and implementing scalable data architectures to support real-time data processing and integration, with a focus on enabling the mission while minimizing cost and complexity.

Collaborat ing with the Data Scientist to effectively deliver data streams of interest and prioritize certain data types for quick analysis.

Develop ing data pipelines to support data integration.

Develop ing and maintain ing data quality checks.

Engag ing with high-priority stakeholders to provide data-driven solutions.

Work ing with downstream data repositories to ensure needs are met and data flow is optimized .

Meet ing the needs of customers unfamiliar with the data or data engineering concepts, including targeters and engineers.

Develop ing data filtering and processing algorithms.

Establishing new data flows to integrate external data sources into Sponsor repositories using AWS methods and non-traditional options.

Ensur ing compliance with relevant data stewardship, documentation, and security r equirements.

Providing technical leadership and direction in implementing enterprise information/data management practices.

Leading and participating in information/data management projects, including the Enterprise Information Architecture, information models and flows, data dictionaries, data standards, and data quality processes and standards.

Developing and maintaining the logical Enterprise Information Architecture that enables seamless information interoperability among transaction systems, document management systems, and information delivery systems.

Must possess and be able to maintain a TS/SCI clearance with polygraph.

Bachelor's d egree (or equivalent experience) in the fields of Computer Science, Information Systems, Engineering, Business, or a related scientific or technical discipline.

BS 10-12, MS 8-10, PhD 5-7

Knowledg e of and experience with the Sponsor’s environment .

Experience with the following: Cloud-based data platforms like AWS, GCP, or Azure.

System architecture and implementation of data solutions.

Data engineering tools and techniques.

Programming languages such as Python, Java, or C++.

B uilding data pipelines and integrating multiple data sources .

W ork ing with challenging data sets and developing data filtering and processing algorithms .

Developing information architectures aligned with information lifecycle management.

Performing conceptual, logical, and physical data modeling using data modeling tools and database design techniques in complex, large-scale data environments.

Transactional data modeling, dimensional modeling, and object - oriented modeling.

Developing scalable entity designs using advanced data structures (e.g., tall tables).

Developing data models that support time dependencies, historical tracking, simple and complex taxonomies, and multilingual data.

Creating data dictionaries, defining metadata management approaches, and establishing governance processes.

Developing and implementing IT architecture plans, Enterprise Information Architecture standards and guidelines, software development methodologies, and strategic plans.

Developing data sharing standards and architecting scalable service - oriented solutions.

Creating enterprise models incorporating master and reference data.

Solid understanding of transaction and information systems, data warehouses, data marts, ODS, MDM methodologies and life cycles, as well as ETL and MDM technologies.

Knowledge of application modeling languages/techniques (e.g., UML, OML, entity relationship modeling, DFDs), including the ability to create and read the associated diagrams.

Desire d

Familiarity with data visualization tools such as Tableau or Power BI .

Experience with machine learning frameworks such as TensorFlow or PyTorch .

Experience with data quality management and data validation techniques .

Ability to work with sensitive data sources and develop data anonymization algorithms .