Data Architect

SteerBridge•Washington, DC

1d•$130,000 - $150,000

About The Position

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.

Requirements

U.S. Citizenship required
Bachelor's degree in Computer Science, Systems Engineering, Data Science, or related field
Must hold, or be able to obtain, a Public Trust clearance (an active Secret or Top Secret clearance also satisfies this requirement)
3+ years of experience in data architecture with demonstrated ownership of enterprise data warehouse design
Strong experience with Python, SQL, Pandas, PySpark, NumPy, Git
Experience with data warehousing technologies such as Databricks, Redshift, BigQuery, Apache Hive
Experience developing and automating large-scale data environments

Nice To Haves

Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn is a plus
Experience designing conceptual, logical, and physical data models
Experience with cloud platforms including AWS, Azure, or GCP
Knowledge of modern data lake and data warehouse architectures
Experience with Apache Kafka, Airflow, Spark, NiFi, or similar technologies
Understanding of big data ecosystems and distributed computing frameworks
Experience supporting AI/ML workflows and analytics platforms
Knowledge of data governance, security, and compliance best practices
Experience with CI/CD pipelines and software development best practices
Experience supporting defense, healthcare, benefits administration, or other mission-critical federal programs preferred

Responsibilities

Design and implement scalable data architectures and data models
Develop and optimize ETL/ELT pipelines supporting analytics and reporting initiatives
Build and maintain cloud-based data platforms and warehousing solutions
Support data integration across multiple structured and unstructured data sources
Collaborate with data scientists, engineers, and stakeholders to support machine learning and analytics initiatives
Implement data governance, security, and quality standards
Monitor and optimize database performance, scalability, and reliability
Support modernization efforts and migration of legacy data environments