> Markdown version of [/jobs/ext/3869461-data-architect](https://www.wearedevelopers.com/jobs/ext/3869461-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Architect - **Company:** SteerBridge Strategies, LLC - **Location:** Washington, DC, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Business Analytics Applications, Systems Engineering, Microsoft Azure, Big Data, Databases, Data Architecture, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, Distributed Systems, Apache Hive, Python (Programming Language), Machine Learning, NumPy, Tensorflow, SQL Databases, Software Organization, Cloud Platform System, Pytorch, Apache Spark, Git, Pandas, Data Lakes, Pyspark, Scikit Learn, Information Technology, Google Bigquery, Apache Kafka, Apache Nifi, Machine Learning Operations, Physical Data Models, Data Pipelines, Amazon Redshift, Databricks - **Published:** October 22, 2026 - **Apply:** https://www.thejobnetwork.com/job/af0eb36a-e157-4bbc-9d08-db8003f1d3a0/data-architect ## About the Role * Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidate must also be able to obtain and maintain the security clearance required for the role, including a Public Trust clearance; an active Secret or Top Secret clearance also satisfies this requirement. * Bachelor's degree in Computer Science, Systems Engineering, Data Science, or a related field. * 3+ years of experience in data architecture, with demonstrated ownership of enterprise data warehouse design. * Strong proficiency with Python, SQL, Pandas, PySpark, NumPy, and Git. * Experience with data warehousing technologies such as Databricks, Amazon Redshift, Google BigQuery, or Apache Hive. * Experience developing and automating large-scale data environments. Preferred Qualifications * Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. * Experience designing conceptual, logical, and physical data models and modern data lake and data warehouse architectures across AWS, Azure, or GCP. * Experience with big data and distributed computing technologies such as Apache Kafka, Airflow, Spark, or NiFi. * Experience supporting AI/ML workflows, analytics platforms, and large-scale data processing environments. * Knowledge of data governance, security, compliance, CI/CD pipelines, and software development best practices. * Experience supporting defense, healthcare, benefits administration, or other mission-critical federal programs. ## Description SteerBridge is seeking a Data Architect (Mid-Level) to support operations and sustainment efforts for the Modern Disability Claims program. This role will focus on designing, building, and maintaining scalable data architectures that support claims intake, adjudication workflows, clinical and claims data integration, and performance analytics for the program. The ideal candidate has hands-on experience designing modern data solutions, developing data pipelines, and supporting enterprise analytics environments within cloud-based ecosystems. Key Responsibilities * Design and implement scalable data architectures and data models that support analytics, reporting, and operational needs. * Develop, maintain, and optimize ETL/ELT pipelines integrating data from multiple structured and unstructured sources. * Build and maintain cloud-based data platforms, data warehouses, and related infrastructure. * Collaborate with data scientists, engineers, and stakeholders to develop data solutions supporting machine learning and advanced analytics initiatives. * Implement and maintain data governance, security, data quality, and integrity standards across data environments. * Monitor and optimize database and data platform performance, scalability, reliability, and availability. * Support data modernization initiatives, including migration and transformation of legacy data environments to modern cloud-based architectures.