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Machine Learning Technologies, LLC is seeking an ETL Developer to design and maintain data pipelines supporting national security missions. You will leverage Python-based workflows to extract, transform, and load data across diverse environments, collaborating with cyber analysts to operationalize datasets.
You will build data cleansing routines, apply SQL analytics, and create dashboards in Tableau/Power BI while ensuring security and governance in cloud and on-prem systems.
As the ETL Developer, you will analyze client challenges and develop innovative solutions by identifying and applying emerging tools and technologies to design and implement new data repositories. You will be responsible for maintaining and expanding the data pipelines that support critical national security missions, as well as managing data and data flows across both existing and new systems. Working closely with our team and cyber analysts, you will apply data engineering expertise to identify, integrate, and operationalize relevant datasets to support mission objectives.
The ideal candidate will have a strong background in Python-based data workflows and experience working in classified Intelligence Community (IC) environments. Additional experience supporting a broad range of data engineering functions, including data extraction, transformation, and loading (ETL), data mapping, data analysis, analytical support, operational support, database support, and the maintenance of data and associated systems.
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.