Data Scientist – Data Mapping & Architecture Support

ECS is seeking a Data Scientist to work remotely.

This role bridges data science and data architecture. The person will map data sources and relationships, build and maintain a company-wide data dictionary, and support the Enterprise Architect in applying policy, standards, and business logic to the overall data framework.

Key Responsibilities

• Data Mapping Identify, trace, and document how data flows across systems - from source to destination - including transformations, dependencies, and ownership.
• Data Dictionary Development Build and maintain a comprehensive data dictionary defining every field, its meaning, format, source, and business context, so teams have one consistent reference.
• Architecture Support Work closely with the Enterprise Architect to translate data mapping and dictionary findings into the technical architecture, ensuring data models reflect real business logic and policy requirements.
• Data Quality & Standards Analyze data for consistency, accuracy, and completeness. Flag gaps or conflicts between systems and recommend standardization.
• Business Logic Validation Partner with business stakeholders (HR, Finance, Operations, etc.) to confirm that documented business rules match how data is actually defined and used.
• Governance Collaboration Support data governance efforts by aligning the data dictionary and mapping work with company policy, compliance needs, and access control requirements.
• Documentation & Reporting Create clear, maintainable documentation (data lineage diagrams, dictionary entries, mapping reports) that both technical and non-technical teams can use.

Salary Range: $120,000 - $130,000

General Description of Benefits

• Experience with data mapping and data lineage tools and techniques
• Strong skills in building and maintaining a data dictionary or metadata repository
• Solid understanding of data modeling concepts (entities, relationships, schemas)
• Proficiency in SQL and at least one programming language (Python preferred)
• Experience working with large, multi-source datasets (databases, APIs, flat files, etc.)
• Ability to interpret business logic and policy and translate it into clear data definitions
• Strong attention to detail and documentation skills