Remote Director, Data Solutions

Ascensus

Raleigh (NC)

In loco

USD 180.000 - 240.000

Tempo pieno

12 ore fa

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Descrizione del lavoro

Ascensus seeks a Director of Data Solutions to lead the data foundation for Ascensus Data & Analytics: architecture, engineering, integration and quality work underpinning enterprise reporting, client-experience analytics, and predictive modeling.

Reporting to the Senior VP, Data & Analytics, you will connect disparate source systems into a connected intelligence layer and lead a team spanning data engineering, data product management and business analysis.

Competenze

10+ years in financial services in data engineering, data management, business intelligence or systems analysis, including at least three years managing a data or reporting team.
Experience owning a recurring, deadline-driven data production cycle (regulatory reporting, capital planning, etc.).
Strong SQL; expertise in ETL/ELT, dimensional and semantic modelling; cloud data platforms; data lineage and quality tooling.
Experience designing, developing, testing and administering internal applications and reporting tools.
Familiarity with Agile Scrum or Kanban; Azure DevOps or Jira for delivery management.
Understanding of predictive, propensity and generative AI in upstream data, including governance.
Experience connecting data investments to business outcomes and communicating value to non-technical leaders.
Able to build cross-functional relationships across Technology, Operations, Product and business teams.
Bachelor's degree required; advanced degree or related certifications preferred.

Mansioni

Define target architecture for shared data environment, including medallion structure and reporting layers.
Build integrated data sets joining sources across the enterprise; deliver trusted client-interaction data and pipelines.
Automate recurring reporting and data preparation; reduce cycle time and manual touchpoints.
Maintain a prioritized data roadmap aligned with analytics and business priorities.
Establish single source of truth; run data quality audits; identify gaps.
Structure and govern data to support predictive analytics and AI workflows.
Coordinate with Technology on data priorities, platform upgrades and support model.
Lead and develop a team spanning data engineering, data product management and business analysis.
Explain technical constraints in business terms to analytics leaders and executives.