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Data Scientist – Data Mapping & Architecture Support

ECS Federal•Work from home, VA
•Remote

About The Position

ECS is seeking a remote Data Scientist whose role bridges data science and data architecture. The position maps data sources and relationships, builds and maintains a company-wide data dictionary, and supports the Enterprise Architect in applying policy, standards, and business logic to the overall data framework. The Data Scientist identifies and documents how data flows across systems, including transformations, dependencies, and ownership. The role develops a consistent reference for data fields, including their meanings, formats, sources, and business context. It also supports the translation of mapping and dictionary findings into technical architecture, checks data quality and business rules, collaborates on governance needs, and creates maintainable documentation for technical and non-technical teams.

Requirements

  • 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, including entities, relationships, and schemas.
  • Proficiency in SQL and at least one programming language; Python is preferred.
  • Experience working with large, multi-source datasets, including databases, APIs, and flat files.
  • Ability to interpret business logic and policy and translate them into clear data definitions.
  • Strong attention to detail and documentation skills.

Nice To Haves

  • Python programming experience.

Responsibilities

  • Identify, trace, and document data flows across systems from source to destination, including transformations, dependencies, and ownership.
  • Build and maintain a comprehensive data dictionary defining each field’s meaning, format, source, and business context.
  • Work with the Enterprise Architect to translate data mapping and dictionary findings into technical architecture and ensure data models reflect business logic and policy requirements.
  • Analyze data for consistency, accuracy, and completeness; identify gaps or conflicts between systems and recommend standardization.
  • Partner with business stakeholders, including HR, Finance, and Operations, to confirm documented business rules match how data is defined and used.
  • Support data governance by aligning data dictionary and mapping work with company policy, compliance needs, and access control requirements.
  • Create maintainable data lineage diagrams, dictionary entries, and mapping reports for technical and non-technical teams.

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