Big Data Architect

Job Title: Senior Big Data Architect Location: Washington, DC – Hybrid – Locals Duration: 12 Months Work Authorisation: USC, GC, GC-EAD and H4-EAD Pay Rate: $80-95/hr. on C2C Mode of Interview: Virtual Position Overview The Data Architecture, Technology, and Analytics (DATA) team within the Client’s Division of Research & Statistics (R&S) is responsible for transforming how enterprise data is ingested, organized, analyzed, and visualized to support economic research and policy decision-making. We are seeking a highly skilled Data Architect / Data Engineer to design, develop, and optimize modern data architectures, enterprise data platforms, and scalable data pipelines. This individual will play a critical role in supporting economists, researchers, analysts, and technical teams by ensuring efficient, reliable, and scalable access to data across the organization. The ideal candidate is a hands-on data professional with deep expertise in data modeling, database architecture, ETL/ELT development, cloud platforms, and enterprise data management. This role requires strong analytical capabilities, excellent communication skills, and a passion for building data solutions that enable advanced research and business intelligence. Key Responsibilities • Design, develop, and maintain enterprise-scale data architectures and data platforms. • Build and optimize scalable ETL/ELT pipelines for ingestion, transformation, and delivery of structured and unstructured data. • Develop conceptual, logical, and physical data models aligned with enterprise architecture standards. • Architect and manage relational databases, data warehouses, data lakes, and modern data ecosystems. • Support migration of data workflows and pipelines between on-premises and cloud environments. • Implement workflow orchestration and automation using tools such as Airflow, Prefect, Dagster, or AWS Step Functions. • Perform data integration across multiple internal and external data sources. • Design and implement Change Data Capture (CDC) solutions for enterprise data warehousing initiatives. • Optimize database performance, scalability, reliability, and data processing workloads. • Collaborate with economists, researchers, analysts, and technical stakeholders to understand business requirements and deliver effective data solutions. • Conduct root cause analysis of data issues and identify opportunities for process improvement and automation. • Implement and maintain CI/CD pipelines and DataOps practices for data engineering projects. • Support machine learning and advanced analytics initiatives through efficient data infrastructure and model deployment frameworks. • Ensure data governance, security, quality, and compliance standards are followed across all solutions. • Document architecture designs, technical specifications, and operational procedures. Required Qualifications Education • Bachelor’s Degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field. • Master’s Degree or other advanced degree is preferred. Experience • Minimum 7+ years of experience in Data Engineering, Data Architecture, Database Engineering, or related fields. • Proven experience designing and implementing enterprise data platforms and large-scale data solutions. Required Technical Skills Data Engineering & Architecture • Strong expertise in data architecture, data modeling, and enterprise information architecture. • Experience designing conceptual, logical, and physical data models. • Extensive experience building and maintaining scalable data pipelines and processing frameworks. • Experience implementing enterprise data warehouses, data lakes, and modern analytics platforms. • Strong understanding of Change Data Capture (CDC) methodologies. Databases • Advanced SQL expertise. • Hands-on experience with: • PostgreSQL • Microsoft SQL Server • MySQL • Experience with database administration, optimization, and performance tuning. Programming & Scripting • Advanced proficiency in: • Python • R • Strong scripting and automation experience. • Experience with additional programming languages such as: • Java • Scala • JavaScript • Perl ETL/ELT & Workflow Automation • Experience designing and automating ETL/ELT processes. • Hands-on experience with workflow orchestration tools such as: • Apache Airflow • Prefect • Dagster • AWS Step Functions Cloud & Modern Data Platforms • Experience working with: • AWS • Microsoft Azure • Snowflake • Experience migrating applications and data pipelines between on-premises and cloud environments. DevOps & DataOps • Experience implementing and maintaining: • CI/CD pipelines • DataOps frameworks • Experience with Git-based source control platforms: • GitHub • GitLab Big Data & Analytics • Experience with: • Distributed computing frameworks • Large-scale data processing systems • High-volume data workloads • Experience processing structured and unstructured datasets. Linux & Infrastructure • Strong development and deployment experience in Linux environments. Preferred Qualifications • Experience working with economic, financial, or regulatory datasets. • Experience supporting research organizations or data-driven policy environments. • Understanding of time-series data modeling, forecasting, and statistical analysis techniques. • Experience with NoSQL technologies and Graph Databases. • Experience developing, deploying, and maintaining Machine Learning models. • Knowledge of enterprise data governance and metadata management frameworks. • Experience supporting advanced analytics and AI-driven data initiatives. Soft Skills • Excellent verbal and written communication skills. • Strong stakeholder management and customer service mindset. • Exceptional analytical and problem-solving abilities. • Ability to work independently and manage multiple priorities simultaneously. • Strong troubleshooting and root-cause analysis skills. • Detail-oriented with a focus on quality and continuous improvement.