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