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Technical Architect - Data Security Clearance

Job in McLean, Fairfax County, Virginia, USA
Listing for: steampunk
Full Time position
Listed on 2026-07-15
Job specializations:
  • IT/Tech
    Data Engineering, Data Warehousing, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
Position: Technical Architect - Data with Security Clearance
Overview We are looking for a seasoned Data Technical Architect to work with our team and our clients to design, architect, and implement enterprise-grade data platforms, services, pipelines, data models, visualizations, and advanced analytics solutions. The Data Technical Architect must be a technologist with excellent communication and customer service skills and a passion for data, innovation, and problem solving. This role spans the full data lifecycle, including data architecture, data engineering, analytics, AI/ML enablement, and cloud platform modernization.

The ideal candidate will provide technical leadership in defining enterprise data strategies, architecting scalable data solutions, and guiding teams through successful implementation. Contributions

Responsibilities include:

* Design greenfield data solution stacks in the cloud or on-premises using modern data services, technologies, and industry best practices.
* Architect the migration and modernization of legacy data environments with a focus on scalability, performance, reliability, and security.
* Define enterprise data architecture standards, integration patterns, and technical roadmaps supporting business and mission objectives.
* Design conceptual, logical, and physical data models to support transactional, analytical, and AI/ML workloads.
* Assess and understand data sources, data models, schemas, data quality requirements, and data workflows to support enterprise data initiatives.
* Assess, understand, and design ETL/ELT processes, data pipelines, orchestration workflows, and data integration solutions.
* Lead architecture reviews and provide technical oversight to engineering teams implementing data solutions.
* Establish data governance, metadata management, data quality, data lineage, and security best practices across enterprise data platforms.
* Assess, understand, and design reporting solutions, business intelligence architectures, data visualization strategies, and executive dashboards.
* Evaluate and recommend BI and analytics platforms, ensuring alignment with business and technical requirements.
* Assess, understand, and design machine learning and AI solutions, MLOps pipelines, and supporting infrastructure for data science teams.
* Address technical inquiries concerning customization, integration, enterprise architecture, and the functionality of data products and platforms.
* Design and implement cloud-based data lakehouse architectures leveraging AWS services or equivalent Azure and GCP technologies.
* Architect solutions involving relational databases, data warehouses, data lakes, streaming platforms, and distributed data systems.
* Collaborate with stakeholders, engineers, data scientists, and business teams to translate requirements into scalable technical solutions.
* Support Agile software development life cycles and modern Dev Sec Ops , DBOps, and MLOps practices.
* Provide technical leadership, mentorship, and architectural guidance to project teams.
* Contribute to the growth and advancement of our AI & Data Exploitation Practice. Qualifications
* Ability to hold a position of public trust with the U.S. Government.
* Bachelor's degree and 10+ years of relevant experience.
* 5+ years of experience designing and architecting enterprise-scale data platforms, data warehouses, data lakes, and lakehouse solutions.
* 5+ years industry experience developing commercial software and solving complex technical challenges.
* 5+ years direct experience delivering enterprise data solutions with technologies such as:
* Big Data Technologies:
Hadoop, Spark, Kafka, Databricks, or other distributed data processing platforms.
* Databases:
Relational databases including PostgreSQL, MySQL, Microsoft SQL Server, and Oracle. No

SQL databases including MongoDB and similar technologies.
* Data Integration & Orchestration:
Airflow, NiFi, or other worklfow orchestration and pipeline management platforms.
* Cloud Platforms: AWS services such as EC2, EMR, RDS, Redshift, Glue, Sage Maker and related analytics services or equivalent Azure and GCP services.
* Streaming Technologies:
Kafka, Spark Structured Streaming, Kinesis, Pub/Sub, Event Hubs, or similar real-time streaming technologies.
* Data Science & Analytics:
Python, R, Databricks or Data preparation, analysis, and machine learning libraries.
* Search Technologies:
Elasticsearch, Solr, Lucene.
* Programming

Languages:

Python, Java, Scala, C++, or other object-oriented and scripting languages.
* Advanced SQL expertise including query authoring, optimization, performance tuning, and complex data analysis.
* Experience developing conceptual, logical, and physical data models.
* Experience defining enterprise data architecture standards, governance frameworks, and integration patterns.
* Experience architecting transactional systems, data warehouses, data lakes, and lakehouse environments.
* Experience with DBOps, MLOps, Dev Ops, and CI/CD practices.
* Experience with message queuing, stream…
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