Data Scientist – Data Mapping & Architecture Support
- Salary
- $120K–$130K
- Hiring from
- United States
- Work type
- Remote
- Posted
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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
