ML Data Engineer

Job TitleThe specific outcome is to build a centralized, reliable, and AI-ready data infrastructure that ensures clean, automated, and trustworthy data flows across Potomac's systems to power their machine learning models and investment decisions.Top Skills RequiredPython & SQL – this is the technical foundation of everythingData Pipeline & ETL/ELT experienceModern Data Platform experience – Data lakes, Data Warehouse or Lakehouse ArchitectureTypical day-to-day responsibilities include:Building and maintaining data pipelines, pulling data in from APIs, trading platforms, SaaS tools, and databases automaticallyCleaning and transforming data, making raw messy data reliable and usable through ETL/ELT processesManaging the data lake/lakehouse, maintaining the central repository where all company data livesBuilding ML-ready datasets, preparing clean structured data so machine learning models can run against itMonitoring data quality, setting up alerts and automated checks to catch data issues before they cause problemsCollaborating with analytics and business teams, translating what the business needs into data solutionsSupporting BI dashboards and reporting, making sure downstream tools like Power BI or Tableau have reliable data feeding themImproving the platform, continuously optimizing pipelines for speed, cost, and reliabilityYears' experience/degree requirements/certification:BS in Computer Science, Data Engineering or related field with 4+ years of experience