Senior Data Engineer
Enterprise Data Architecture & Data Modeling ExpertiseDesign and maintain scalable data architectures, data lakes, data warehouses, and logical/physical/conceptual data models that support enterprise analytics and operations. Advanced Data Engineering & ETL/ELT DevelopmentBuild, optimize, and automate ETL/ELT processes, data integration pipelines, and large-scale data processing frameworks for structured and unstructured data. Strong SQL, Python, and Big Data Experience7+ years of experience with enterprise data platforms, advanced SQL, Python programming, distributed computing, and big data processing systems. Workflow Automation, Cloud, and DataOpsExperience with orchestration tools such as Airflow, Prefect, Dagster, or AWS Step Functions, plus cloud platforms and CI/CD/DataOps practices. Leadership, Troubleshooting & Cross-Functional CollaborationAbility to solve complex data issues, support modernization initiatives, mentor team members, and work closely with business and technical stakeholders to deliver scalable solutions.Place of Performance: on location in Washington, DCPeriod of Performance: end of the year with likely extensionCitizenship: U.S. Citizen only Work Authorization - USC only Duration: to the end of the year with likely extensions Contract through Year End - Strong likelihood of extension Onsite Location: New York Ave NW, Washington, DC 20006 5 days a week until further notice. Position Title: Senior Data Engineer / Data Architect Location Information Washington, D.C. Position Responsibilities: As a Senior Data Engineer / Data Architect, you will play a pivotal role in designing, building, optimizing, and maintaining modern data platforms and data integration solutions that support enterprise analytics, reporting, research, and operational initiatives. You will leverage your expertise in data modeling, database design, and workflow automation to provide scalable, reliable, and efficient data solutions. In this position, you will collaborate with various teams and stakeholders to deliver data-driven technologies that enable organizational growth and data-informed decision-making. Key responsibilities include:Designing, developing, and maintaining scalable enterprise data architectures, databases, data lakes, and data warehouse solutions.Building, optimizing, and automating ETL/ELT processes as well as data integration pipelines.Developing and maintaining robust data processing frameworks to handle both structured and unstructured data sources.Designing and implementing logical, physical, and conceptual data models tailored to business and analytical requirements.Ensuring data quality, integrity, governance, and security across enterprise data environments.Monitoring and optimizing database performance, storage utilization, and data processing workloads.Developing and implementing workflow orchestration and automation solutions to support data operations and analytics.Collaborating with cross-functional teams to gather requirements and deliver scalable, reliable data solutions.Performing root cause analysis and troubleshooting for data-related issues to enhance operational efficiency.Supporting cloud migration initiatives and modernization projects involving data platforms and pipelines.Implementing and maintaining CI/CD processes, DataOps practices, and deployment automation.Documenting technical designs, architectural decisions, data flows, and operational procedures.Evaluating emerging technologies to recommend and implement improvements to data infrastructure and engineering approaches.Providing technical leadership, guidance, and mentorship to junior members and project teams. Essential Skills, ExperienceBachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related technical field.At least 7 years of experience in data engineering, data architecture, database administration, or closely related fields.Expertise in designing, developing, and optimizing enterprise data pipelines and integration solutions.Advanced proficiency with SQL and relational database systems (e.g., PostgreSQL, SQL Server, MySQL).Strong programming skills with Python and experience with scripting languages used in data engineering and analytics.Hands-on experience managing large-scale data environments, distributed computing, and big data processing systems.Proficiency with workflow orchestration and automation tools (e.g., Apache Airflow, Prefect, Dagster, AWS Step Functions).Experience developing and supporting data solutions in Linux-based environments.Familiarity with source control and collaboration tools such as GitHub and GitLab.Strong analytical, troubleshooting, and problem-solving abilities.Excellent written and verbal communication skills with the ability to relay technical concepts to diverse audiences. Preferred Experience/Skills:Advanced degree in Computer Science, Data Science, Engineering, or a related discipline.Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).Knowledge of Snowflake or other modern cloud data platforms.Experience with NoSQL and graph databases.Experience implementing enterprise data warehouses and Change Data Capture (CDC) methodologies.Background in migrating data platforms and workflows between on-premises and cloud environments.Experience with CI/CD pipelines and DataOps best practices.Experience developing, deploying, and maintaining machine learning solutions.Understanding of time-series data, forecasting models, and advanced analytics.Experience supporting research, financial, regulatory, healthcare, public sector, or other data-intensive domains.Working knowledge of additional programming languages (Java, Scala, JavaScript, Perl, etc.). Core Competencies:Data Architecture & ModelingData Engineering & IntegrationDatabase Design & AdministrationCloud Data PlatformsETL/ELT DevelopmentWorkflow AutomationData Governance & QualityDataOps & CI/CDPerformance OptimizationProblem Solving & TroubleshootingCross-Functional CollaborationTechnical Leadership