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# Data Engineer

- **Company:** Adams, Inc.
- **Location:** Washington, DC, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Databases, Extract Transform Load (ETL), Data Transformation, Relational Databases, Database Queries, Database Schema, Python (Programming Language), PostgreSQL, Machine Learning, MySQL, NumPy, SQL Databases, Unstructured Data, Jupyter Notebook, Pandas, Scikit Learn, HuggingFace, Api Design
- **Published:** September 26, 2026
- **Apply:** https://www.juju.com/job/18_5339_262826

## About the Role

* Strong Python and SQL proficiency.
 * Hands-on experience designing and maintaining ETL pipelines and conducting exploratory data analysis.
 * Experience with Pandas and NumPy, relational databases including PostgreSQL and MySQL, data modeling, database schemas, and data transformation.
 * Ability to work with structured and unstructured datasets while ensuring accuracy, quality, and reliability.
 * Familiarity with Jupyter Notebook, VS Code, or PyCharm.
 * Strong analytical, problem-solving, and communication skills.
 * Exposure to AI and machine-learning workflows is valued, including scikit-learn, Hugging Face Transformers, the OpenAI API or similar platforms, AI/ML dataset management, and collaboration with researchers or data scientists.

## Description

* Design, develop, and maintain scalable ETL pipelines.
 * Collect, clean, transform, and organize structured and unstructured data.
 * Perform exploratory data analysis to identify trends, patterns, anomalies, and data-quality issues.
 * Prepare datasets for AI and machine-learning initiatives in partnership with research, data science, and engineering teams.
 * Develop and maintain data models, database schemas, and data-storage solutions.
 * Write and optimize SQL queries for extraction, transformation, and analysis.
 * Maintain data quality, integrity, consistency, and security across pipelines and databases.
 * Automate validation, reporting, and recurring data-processing workflows.
 * Document pipelines, processes, and technical decisions, and troubleshoot data or pipeline failures.


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