Enterprise Architect - Data Engineer

Arcfield is seeking an Enterprise Architect - Data Engineer to lead scalable data architecture and enterprise information/data management practices for a sponsor mission.

Responsibilities

• Design and implement scalable data architectures for real-time data processing and data integration, balancing mission enablement with cost and complexity reduction.
• Collaborate with the Data Scientist to deliver data streams of interest and prioritize data types for faster analysis.
• Develop data pipelines to support data integration.
• Develop and maintain data quality checks.
• Engage high-priority stakeholders with data-driven solutions.
• Work with downstream data repositories to ensure stakeholder needs are met and data flow is optimized.
• Support customers who are unfamiliar with data or data engineering concepts, including targeters and engineers.
• Develop data filtering and processing algorithms.
• Establish new data flows to integrate external data sources into Sponsor repositories using AWS methods and non-traditional options.
• Ensure compliance with data stewardship, documentation, and security requirements.
• Provide technical leadership and direction for implementing enterprise information/data management practices.
• Lead and participate in information/data management projects, including:
  • Enterprise Information Architecture
  • Information models and flows
  • Data dictionaries
  • Data standards
  • Data quality processes and standards
• Develop and maintain the logical Enterprise Information Architecture to enable interoperability among transaction systems, document management systems, and information delivery systems.

Requirements

• Maintain a TS/SCI clearance with polygraph.
• Bachelor’s degree (or equivalent experience) in Computer Science, Information Systems, Engineering, Business, or a related scientific or technical discipline.
• Education level guidance: BS 10-12, MS 8-10, PhD 5-7.
• Knowledge and experience with the Sponsor’s environment.
• Experience with cloud-based data platforms: AWS, GCP, or Azure.
• System architecture and implementation of data solutions.
• Data engineering tools and techniques.
• Programming languages: Python, Java, or C++.
• Build data pipelines and integrate multiple data sources.
• Work with challenging datasets and develop data filtering and processing algorithms.
• Develop information architectures aligned with information lifecycle management.
• Perform conceptual, logical, and physical data modeling using data modeling tools and database design techniques in complex, large-scale data environments.
• Experience with transactional data modeling, dimensional modeling, and object-oriented modeling.
• Develop scalable entity designs using advanced data structures (e.g., tall tables).
• Develop data models supporting time dependencies, historical tracking, simple and complex taxonomies, and multilingual data.
• Create data dictionaries, define metadata management approaches, and establish governance processes.
• Develop and implement IT architecture plans, including Enterprise Information Architecture standards and guidelines, software development methodologies, and strategic plans.
• Develop data sharing standards and architect scalable service-oriented solutions.
• Create enterprise models incorporating master and reference data.
• Solid understanding of transaction and information systems, data warehouses, data marts, ODS, MDM methodologies and life cycles, plus ETL and MDM technologies.
• Knowledge of application modeling languages/techniques such as UML, OML, entity relationship modeling, and DFDs, including the ability to create and read associated diagrams.

Technologies

• AWS
• GCP
• Azure
• Python
• Java
• C++
• TensorFlow
• PyTorch
• Tableau
• Power BI
• UML
• OML
• Entity relationship modeling
• DFDs
• ETL
• MDM
• Data modeling tools
• Data dictionaries

Location

• McLean, VA
• Onsite

Compensation

• USD 125,133 - 217,582 per year

Benefits

• Health Insurance
• Life Insurance
• Paid Time Off
• Holiday Pay
• Short Term and Long-Term Disability
• Retirement and Savings
• Learning and Development opportunities
• wellness programs
• other optional benefit elections

Desired

• 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.