Client Experience Technical Product Owner

Vanguard•Malvern, PA

2d•Hybrid

About The Position

Leads the strategic vision and roadmap for a technical product or products with cross-divisional impact, demonstrating a deep understanding of the product(s) and associated business areas. Products often have enterprise-wide implications. Overall Description: (75%) Manages technical strategy (& implementation) for Client Experience data products (both client feedback survey data & non-survey data) and owns Data Dependency monitoring/alerts ecosystem, in partnership with technical, analytics, and product owner stakeholders across the division. (25%) Manages analytics data (including SQL code for senior leadership OKRs), and ensures data quality and data governance standards are achieved and communicated, supporting analytics stakeholders across the division. Technical Responsibilities: Leads development and implementation of new technical cross-divisional products. Influences and collaborates, across cross-functional technical teams, to optimize data quality and data governance ecosystem. Drives connections across data products / capabilities (data capture, analytics, reporting, engineering, operations, SQL management, etc.). Builds (& leads) the team’s “Data Dependency” program (including documentation, monitoring capabilities, alert functionalities, technical process maps), and required communications plans. Analytics Responsibilities: Engages with internal analytics partners to understand business strategy, objectives, and KPIs. Leads “Monthly Data QA” (ensuring key metrics across multiple data ecosystems match), annual SQL code optimization initiatives, regular ROI analyses, regular impact analyses, and ongoing partnerships with other analysts to continuously enhance all of the above. Manages a series of senior leadership OKR Metrics (& respective SQL code) to ensure optimal data quality & data governance practices.

Requirements

Strong communication skills
Strong strategy experience
Client Experience (CX) background
Financial Industry background
Data Engineering
Data Quality
Data Lineage
Data Governance
Metadata Documentation
Technical Process Maps
Data Dependency Identification/Mapping
Data Architecture
SQL
Python
Power BI
Tableau
AWS S3 Tables
Github
running formal Experiments and ROI analyses
Undergraduate degree or equivalent combination of training and experience required.
Minimum of eight years related business experience.

Nice To Haves

Graduate degree preferred.
Three years of leading large cross-functional teams on major organizational projects preferred.

Responsibilities

Manages technical strategy (& implementation) for Client Experience data products (both client feedback survey data & non-survey data) and owns Data Dependency monitoring/alerts ecosystem, in partnership with technical, analytics, and product owner stakeholders across the division.
Manages analytics data (including SQL code for senior leadership OKRs), and ensures data quality and data governance standards are achieved and communicated, supporting analytics stakeholders across the division.
Leads development and implementation of new technical cross-divisional products.
Influences and collaborates, across cross-functional technical teams, to optimize data quality and data governance ecosystem.
Drives connections across data products / capabilities (data capture, analytics, reporting, engineering, operations, SQL management, etc.).
Builds (& leads) the team’s “Data Dependency” program (including documentation, monitoring capabilities, alert functionalities, technical process maps), and required communications plans.
Engages with internal analytics partners to understand business strategy, objectives, and KPIs.
Leads “Monthly Data QA” (ensuring key metrics across multiple data ecosystems match), annual SQL code optimization initiatives, regular ROI analyses, regular impact analyses, and ongoing partnerships with other analysts to continuously enhance all of the above.
Manages a series of senior leadership OKR Metrics (& respective SQL code) to ensure optimal data quality & data governance practices.