ML Data Engineer (100% On-Site |Contract-to-hire)

About the role

Potomac is a boutique tactical asset manager headquartered in Bethesda, MD. We combine institutional-grade investment expertise with a quantitative process that is Built to Conquer Risk®. We are seeking a Machine Learning Data Engineer to join our team.

Responsibilities

• Design, build, and maintain scalable data pipelines to ingest data from multiple internal and external sources (APIs, SaaS platforms, databases, files).
• Develop and manage a centralized data lake / lakehouse to standardize and curate data for analytics, reporting, and machine learning use cases.
• Implement ELT/ETL processes to clean, validate, transform, and model data into trusted datasets.
• Build and maintain machine-learning–ready datasets and feature pipelines that support experimentation and production models.
• Ensure data quality, freshness, and reliability through monitoring, alerting, and automated validation checks.
• Partner with analytics and business teams to define data requirements, metrics, and reporting outputs.
• Support downstream data consumption for BI tools, dashboards, operational reporting, and partner data exports.
• Apply best practices around data governance, security, access controls, and documentation.
• Collaborate cross-functionally to deliver scalable, maintainable data solutions aligned with business priorities.
• Continuously improve performance, cost efficiency, and reliability of the data platform.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Engineering, or a related field (or equivalent experience).
• 4+ years of experience in data engineering or related roles.
• Strong proficiency in Python and SQL.
• Hands-on experience building and operating data pipelines and workflows.
• Experience with modern data platforms (data lakes, data warehouses, or lakehouse architectures).
• Familiarity with orchestration tools (e.g., Airflow, Dagster, Prefect) and data transformation frameworks.
• Solid understanding of data modeling, schema design, and data quality best practices.
• Experience integrating data from APIs and third-party systems.
• Strong problem-solving skills and ability to work independently in a fast-paced environment.
• Excellent communication skills and ability to work with both technical and non-technical stakeholders.
• Experience supporting machine learning workflows (feature engineering, training datasets, or ML pipelines).
• Familiarity with cloud platforms (AWS, Azure, or GCP).
• Experience with streaming or near–real-time data pipelines.
• Knowledge of data governance, security, and compliance best practices.
• Prior experience in financial services, fintech, or regulated data environments.
• Experience working in a high-growth or startup environment.

Qualifications

• Experience in financial services, fintech, or regulated data environments is preferred.
• Prior experience in a high-growth or startup environment is preferred.

Skills

• Python
• SQL
• Data modeling
• Data transformation
• ELT/ETL processes
• Data governance
• Data security
• Cloud platforms (AWS, Azure, or GCP)
• Streaming or near–real-time data pipelines

Benefits

• Competitive compensation package including base salary ranging from $120,000 to $140,000 per year.
• Flexible work schedule.
• Professional development opportunities.
• Health insurance benefits.
• Retirement savings plans.

Pay

The pay range for this role is: $120,000 - $140,000 USD per year (US).

Schedule

Flexible work schedule.

Operations

Bethesda, MD