> Markdown version of [/jobs/ext/3962815-data-scientist-senior-raleigh-nc-hybrid](https://www.wearedevelopers.com/jobs/ext/3962815-data-scientist-senior-raleigh-nc-hybrid). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist- Senior :: Raleigh, NC (Hybrid) - **Company:** ARK Solutions, Inc. - **Location:** Raleigh, NC, United States - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** Business Analytics Applications, Data Governance, Document-Oriented Databases, Metadata, Data Streaming, Data Ingestion, Azure Data Factory, Databricks - **Published:** October 27, 2026 - **Apply:** https://www.careerjet.com/job/us60ebce2bb5d2a3a89967491546af50fb/eaa ## About the Role * Ability to define and standardize enterprise data elements, lineage, and business rules across units. (3 Years) * Ability to collaborate with business teams to translate data needs into enterprise standards. (3 Years) * Ability to implement governance practices including metadata, lineage, and data quality. (3 Years) * Ability to document end-to-end data flows across systems. (3 Years) ## Description Seeking for a Senior Data Scientist to support the expansion of our enterprise data capabilities using Azure Databricks, Azure Data Factory, and modern analytics platforms. This role involves establishing consistent data practices across technical teams and business units, focusing on data ingestion, transformation, cleansing, and analytics solutions. Responsibilities: * Partner with business stakeholders and technical teams to understand data needs and identify improvement opportunities. * Facilitate discussions to identify authoritative data sources and improve understanding of enterprise data assets. * Incorporate data governance, metadata, lineage, and data quality practices into projects. * Standardize and reuse data ingestion, transformation, cleansing, and validation patterns across projects. * Develop and maintain an inventory of enterprise data assets, including data owners and system relationships. * Document data flows across applications and platforms to promote consistency and scalability.