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EI

Potomac Fund Management ML Data Engineer

Expert In Recruitment Solutions
πŸ‡ΊπŸ‡Έ United States
On-site
3 weeks ago
  • Python
  • SQL
  • ETL
  • ELT
  • AI
  • Machine Learning
  • Power BI
  • Tableau
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Required - Top 3:
  1. Python & SQL – this is the technical foundation of everything
  2. Data Pipeline & ETL/ELT experience
  3. Modern Data Platform experience – Data lakes, Data Warehouse or Lakehouse Architecture

Specific Outcome This Position Will Produce:The 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.

Typical Day-to-Day:
  • Building and maintaining data pipelines, pulling data in from APIs, trading platforms, SaaS tools, and databases automatically
  • Cleaning and transforming data, making raw messy data reliable and usable through ETL/ELT processes
  • Managing the data lake/lakehouse, maintaining the central repository where all company data lives
  • Building ML-ready datasets, preparing clean structured data so machine learning models can run against it
  • Monitoring data quality, setting up alerts and automated checks to catch data issues before they cause problems
  • Collaborating with analytics and business teams, translating what the business needs into data solutions
  • Supporting BI dashboards and reporting, making sure downstream tools like Power BI or Tableau have reliable data feeding them
  • Improving the platform, continuously optimizing pipelines for speed, cost, and reliability

Potomac Fund Management ML Data Engineer Β· Expert In Recruitment Solutions

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