Data Engineer

Data Engineer

Washington, DC

Pay From: $60.00 per hour

• 7+ years of related experience; advanced degree preferred.
• Advanced working knowledge of SQL and experience working with relational database platforms including PostgreSQL, Microsoft SQL Server, and MySQL.
• Advanced working knowledge of Python, R, and other scripting languages used for data engineering and analytics.
• Working knowledge of additional programming and scripting languages such as Java, Scala, JavaScript, or Perl.
• Experience working with large‑scale data systems, including distributed computing, scalable data processing, data storage architecture, and optimization of high‑volume data workloads.
• Experience designing, developing, and automating ETL/ELT workflows and data integration pipelines.
• Experience building, optimizing, and maintaining scalable databases, data pipelines and data processing frameworks.
• Bachelor's degree in computer science, Information Technology, Engineering or a related technical field.

• Support Architecture, Technology, and Analytics (DATA) section with transforming the Research & Statistics (R&S) ingests, organizing, using, and visualizing data.
• Expand and optimize data and data pipeline architecture, as well as optimizing data flow and collection for economic policy and research teams.
• Be an experienced hands‑on data modeler with working knowledge of database design and administration, data pipeline building, and data wrangling, improving existing data systems and/or building them from the ground up.
• Support economists and technical experts and ensure optimal data delivery architecture is designed and developed.
• Be excited by the prospect of optimizing or re‑designing the R&S division's data architecture to support next generation of data initiatives.
• Work with workflow orchestration and pipeline automation tools such as Apache Airflow, Prefect, Dagster, or AWS Step Functions.
• Migrate workflows and data pipelines between on‑premises and cloud environments.
• Process, analyze, and integrate structured and unstructured data sources.
• Develop in Linux environments and use source control platforms such as Git Lab and/or Git Hub.
• Perform root cause analysis on internal and external data and business processes to answer business questions and identify opportunities for improvement.
• Design and communicate enterprise information architecture at conceptual, logical, and physical levels.
• Design and implement database, data lake, and enterprise data platform solutions.
• Provide strong hands‑on software engineering and implementation experience, including development, testing, and deployment of data applications and services.
• Exhibit excellent oral and written communication skills with strong customer service orientation, analytical, problem‑solving, and troubleshooting skills.
• Understand time series data and related analytical and forecasting techniques.
• Work in a research environment and/or with economic or financial data.
• Use No
  
  SQL and graph database technologies.
• Develop, train, deploy, and maintain machine learning models.
• Work with cloud technologies such as AWS, Microsoft Azure, and Snowflake.
• Implement data warehouses utilizing Change Data Capture (CDC) methodologies.
• Implement and maintain CI/CD pipelines and Data Ops platforms.

Quadrant is an affirmative action/equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, status as a protected veteran, or status as an individual with a disability.

Healthcare benefits are offered to all eligible employees according to compliance mandated by the Affordable Care Act.