Director, Data Solutions

Ascensus•Needham, MA

About The Position

The Director, Data Solutions leads the data foundation for Ascensus Data & Analytics, including architecture, engineering, integration and quality work that supports enterprise reporting, client-experience analytics and predictive modeling. The role connects disparate source systems into a shared intelligence layer, enabling teams to use trusted data across the enterprise. Reporting to the Senior Vice President, Data & Analytics, the Director leads a team spanning data engineering, data product management and business analysis. The position partners with Technology on data priorities, pipeline delivery and platform standards, beginning with the Retirement business line, and works with analytics leaders and business stakeholders to sequence priorities. The Director defines the target architecture and standards for the shared data environment; develops integrated, reusable data sets; automates manual reporting and preparation work; and maintains a prioritized data roadmap. The role establishes enterprise data definitions and quality practices, prepares data for predictive and emerging agentic applications, and coordinates with Technology on platform upgrades, support and architectural decisions. It also leads and develops the team, communicates technical trade-offs and delivery risks to stakeholders, and safeguards confidential data. Ascensus expects associates to embrace emerging technologies and practices that advance its mission and client commitments. Its Core Values are People Matter, Quality First and Integrity Always. For virtual remote positions, the company requires an uninterrupted workspace, family care during business hours, and internet speed of at least 25 Mbps for individual use; a stronger connection may be needed when shared. The posting also provides guidance about internet connectivity for call center roles, although this position is not identified as a call center role.

Requirements

10 or more years of experience in financial services in data engineering, data management, business intelligence or systems analysis.
At least three years of experience managing a data or reporting team.
Experience owning a recurring, deadline-driven data production cycle, such as regulatory reporting, capital planning or stress testing submissions, financial close or executive reporting, and responsibility for streamlining it over successive cycles.
Strong SQL skills, including optimization of complex queries and tuning of stored procedures.
Proficiency in ETL/ELT and pipeline design, dimensional and semantic modeling, and modern cloud data platforms.
Experience with layered data architectures, data lineage and data-quality tooling.
Experience designing, developing, testing and administering internal applications and reporting tools, including replacing vendor products when an internal solution better serves the business.
Experience with software development lifecycle methodologies such as Agile Scrum or Kanban, using tools such as Azure DevOps or Jira for requirements and delivery management.
Practical understanding of the upstream data needs of predictive, propensity and generative AI use cases, including structure, granularity, freshness, lineage and governance.
Ability to connect data investments to commercial outcomes and explain the value and trade-offs of foundational work to non-technical leaders.
Proven ability to build working relationships across Technology, Operations, Product and business teams, and to exercise good judgment independently.
Bachelor's degree in Computer Science, Information Systems, Engineering, Finance or a related field, or equivalent work experience.
For virtual remote work: ability to maintain an uninterrupted workspace, arrange family care during business hours, and meet the stated internet-speed requirement.

Nice To Haves

Working familiarity with the Microsoft data stack used at Ascensus, including SQL Server, SSIS, SSAS and Power BI semantic models.
Experience in retirement, wealth management, asset management, banking or fintech.
An advanced degree or relevant data platform certifications.

Responsibilities

Define the target architecture for the shared data environment, including its layered medallion structure, semantic models and reporting layers, in partnership with Technology and enterprise architecture.
Set and enforce standards for pipeline design, source control, testing, deployment and documentation.
Build integrated enterprise data sets, prioritizing client interactions, book of business, customer experience, behavioral trends, and product and partner definitions.
Deliver a shared client-interaction source spanning digital, workflows, interactions and sentiment, and an advisor data pipeline connecting core platform data with CRM sales activity.
Automate manual, repetitive reporting and data-preparation work; track and reduce cycle time and manual touchpoints for recurring deliverables.
Maintain a prioritized data roadmap with the data product owner, aligned to analytics and business priorities.
Build, document and assign owners to reusable data sets so teams can share them rather than rebuild them for individual projects.
Establish a single source of truth for enterprise reporting and client insight, maintain consistent enterprise data definitions, conduct data-quality audits, and identify foundational system gaps.
Structure and govern data for predictive and propensity modeling and emerging agentic workflows in collaboration with data science and analytics teams.
Coordinate with Technology on data priorities, platform upgrades and the ongoing support model; represent Data & Analytics requirements in architectural reviews and influence scalable, consistent decisions.
Lead, coach and develop a team spanning data engineering, data product management and business analysis; set delivery and engineering expectations, mentor through code and design reviews, and build team capacity.
Explain technical constraints and trade-offs in business terms, and communicate status, dependencies and risks early to stakeholders and executives.
Adopt and protect emerging technologies, platforms and practices that support transformational growth and Ascensus' mission and client commitments.
Protect and properly handle confidential Ascensus data to prevent unauthorized access, improper transmission or unapproved disclosure.