Description

Design and optimize large-scale data pipelines, database architectures, and analytics platforms to support economic research and policy teams.

This role is on-site.

Responsibilities

• Design and implement scalable data storage architectures, data lakes, and enterprise data platforms.
• Build, automate, and optimize ETL/ELT workflows and data integration pipelines using modern orchestration tools.
• Develop and maintain high-volume data processing frameworks for structured and unstructured data sources.
• Migrate workflows between on-premises and cloud environments while ensuring performance and reliability.
• Perform root cause analysis on data processes and implement CI/CD pipelines for data applications.

Required Skills

• Bachelor’s degree in Computer Science, IT, Engineering, or related field with 7+ years of experience.
• Advanced SQL proficiency with PostgreSQL, Microsoft SQL Server, and MySQL.
• Strong Python and R scripting for data engineering and analytics.
• Experience with distributed computing, scalable data processing, and high-volume workload optimization.
• Proficiency with workflow orchestration tools like Apache Airflow, Prefect, Dagster, or AWS Step Functions.
• Hands-on experience with Linux environments, GitLab, and GitHub.
• Working knowledge of cloud technologies including AWS, Microsoft Azure, and Snowflake.
• Experience with NoSQL, graph databases, and Change Data Capture (CDC) methodologies.

Preferred Skills

• Advanced degree in a technical field.
• Experience with machine learning model development, training, and deployment.
• Knowledge of Java, Scala, JavaScript, or Perl.

Key Skills

Education

Bachelor's degree