NCDIT-T WEB is seeking a Data Scientist - Senior to support the NCDIT-T / NCDOT’s rapid expansion of its enterprise data capabilities through Azure Databricks, Azure Data Factory, and modern analytics platforms. This contractor will be a dedicated resource focused on establishing consistent enterprise data practices that span both technical teams and business units as they are building data ingestion, transformation, cleansing and analytics solutions.
The contractor will provide the organization with an experienced consultant who can work directly and collaboratively with business units to understand how they define, interpret, and use their data, and then translate those needs into consistent enterprise standards. This role will help refine business-critical data elements, improve data definitions and lineage, and establish reusable patterns that align both technical and business perspectives. By partnering closely with business owners, the consultant will strengthen data quality, improve confidence in enterprise data, and reduce friction caused by inconsistent or unclear business rules.
The ideal candidate has advanced, specialized expertise in enterprise data strategy, governance, and modern data architecture that cannot be performed by an earlycareer resource. The position is responsible for establishing foundational, organizationwide data management practices and must operate as the initial member of a new Data Strategy & Governance function. This requires a high level of independent judgment, architectural leadership, and handson experience with complex data platforms.
Key Responsibilities:
Partner with business stakeholders, application teams, Database Administration, Data Engineering, Power BI, and project teams to understand data needs and identify opportunities for improvement.
Work with project teams to incorporate practical data governance, metadata, lineage, and data quality practices into ongoing initiatives.
Identify opportunities to standardize and reuse data ingestion, transformation, cleansing, and validation patterns across projects using Azure Data Factory and Azure Databricks.
Help develop and maintain an inventory of enterprise data assets, including data owners, stewards, business definitions, and system relationships.