Section 1: Position Summary
The Director, Data Solutions leads the data foundation for Ascensus Data & Analytics: the architecture, engineering, integration and quality work that enterprise reporting, client-experience analytics and predictive modeling all depend on. The role is accountable for connecting disparate source systems into a connected intelligence layer, so insight can be drawn across the enterprise rather than one system at a time, and so analytics teams build on trusted data instead of assembling it themselves.
The Director reports to the Senior Vice President, Data & Analytics and leads a team spanning data engineering, data product management and business analysis. The role works closely with Technology on data priorities, pipeline delivery and platform standards, starting with the Retirement business line, and with analytics leaders and business stakeholders on sequencing what gets built first.
Section 2: Job Functions, Essential Duties and Responsibilities
Data Architecture & Technical Direction: Define the target architecture for our shared data environment, including the layered (medallion) structure, semantic models and reporting layers, working with Technology and enterprise architecture. Set standards for pipeline design, source control, testing, deployment and documentation, and hold the team to them.
Connected Data Sets & Integration: Build the integrated data sets that join sources across the enterprise. Near-term priorities include client interactions, book of business, customer experience and behavioral trends, and product and partner definitions with a reliable source of truth. Deliver the shared client-interaction source covering digital, workflows, interactions and sentiment, and the advisor data pipeline connecting core platform data with CRM sales activity.
Process Efficiency & Automation: Automate the manual, repetitive reporting and data preparation work that consumes capacity today. Track cycle time and manual touchpoints on recurring deliverables and reduce both.
Data Products & Roadmap: Work with the data product owner to maintain a prioritized data roadmap tied to analytics and business priorities. Build data sets once, document them, assign owners, and make them reusable across teams instead of rebuilt per project.
Data Quality & Governance: Establish a single source of truth for enterprise reporting and client insight. Maintain enterprise data definitions so key terms mean the same thing across lines of business. Run data quality audits, and identify gaps in foundational systems that block enterprise-wide reporting and cross-sell insight.
AI & Advanced Analytics Enablement: Structure and govern data to support predictive and propensity modeling and emerging agentic workflows, working with data science and analytics early enough that the foundation is ready when the models are.
Technology Partnership: Act as the main point of coordination with Technology on data priorities, platform upgrades and the ongoing support model. Represent Data & Analytics requirements in architectural review and influence decisions so solutions stay consistent and scalable across teams.
Team Leadership & Development: Lead, coach and develop a team spanning data engineering, data product management and business analysis. Set clear expectations for engineering discipline and delivery, mentor through code and design review, and build the bench as the function grows.
Stakeholder Communication: Explain technical constraints and trade-offs in plain business terms to analytics leaders, business stakeholders and executives, and communicate status, dependencies and risk early.
General
Proactively adopt, protect and boldly embrace emerging technologies (AI, automation, etc.), platforms, and evolving practices that accelerate transformational growth and advance Ascensus’ mission and client commitments.
Responsible for protecting, securing, and proper handling of all confidential data held by Ascensus to ensure against…