Data Management Lead
Listed on 2026-05-27
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IT/Tech
Data Analyst, Data Engineering
US:
AR:
BENTONVILLE | Information Technology | Full Time
107, USD per year
DescriptionPay is based on a number of factors including the successful candidate’s job-related knowledge and skills, qualifications, and prior experience. Arvest offers a comprehensive suite of benefits, including a full range of health and life, financial, and wellness benefits. For more information about benefits, please refer to the company's benefits page.
Position is Monday through Friday from 8 am to 5 pm Central Time with the ability to work additional hours as project needs demand.
Incumbent should reside within the Arvest 4 State Footprint (AR, KS, MO, OK)
Job SummaryThe Experience Data Management Lead is the technical architect of the Customer and Associate Experience (EXP) data ecosystem. You will bridge the gap between raw data engineering and executive-level storytelling by ensuring the integrity of data pipelines, pressure-testing analytical models, and mentoring junior analysts in data analysis and management best practices. You are responsible for transforming massive volumes of structured and unstructured feedback into a reliable, high-integrity 'engine room' that powers the bank’s strategic decisions.
Responsibilities- Act as an advisor to business leaders on the customer and associate experience based on in-depth knowledge and analysis of experience data from feedback loops at a product, channel, journey or relationship level. Sharing experience insights, drivers and trends over time that are relevant to the business strategy, insightful and actionable.
- Oversee the synthesis of solicited and unsolicited feedback using Natural Language Processing (NLP), statistical modeling (regression/correlation), and sentiment analysis to identify actionable drivers of customer loyalty or associate engagement.
- Act as the subject matter expert for junior analysts, providing guidance on querying, joining, and transforming large datasets, as well as curiosity, investigation and explainability when numbers or metrics change significantly.
- Lead the Data Ops function to ensure the integrity of CX/AX data pipelines, maintaining strict standards for data structures, documentation, and dashboard accuracy.
- Create and maintain automated, enterprise-wide dashboards and 'State of the Experience' reports that connect experience KPIs to foundational bank metrics. Establishing best practices for quality testing, publishing and monitoring dashboards and reports.
- Oversee the integrations and maintain strong relationships with those who own source system data needed to complete the experience analysis and reporting. Manage the technical relationship with survey and analytics platform vendors (e.g., Qualtrics), overseeing vendor roadmaps, platform enhancements, and technical issue resolution.
- Understand and comply with bank policies, laws, regulations, and the bank's BSA/AML Program, as applicable to job duties. This includes, but is not limited to, completing compliance training, adhering to internal procedures and controls, reporting any known violations of compliance policies, laws, or regulations, and reporting any suspicious customer and/or account activity.
- Other duties and special projects may be assigned.
- Required:
6 years of experience as a data scientist, advanced insights analysis or data management, with a focus on experience or behavioral data. Including structured and unstructured data, preferably in a lead or senior capacity. - Required:
Data Engineering Mastery of SQL for querying and transforming large datasets; experience with Python, R, CSS, or HTML/JS. - Required:
Proven ability to work in depth with Google Big Query, Tableau, and other business data sources, including Salesforce, Marketing Cloud and traditional banking platforms. - Required:
Visualization, advanced skills in building automated dashboards and BI tools to turn 'metrics on a page' into visual stories. - Required:
Demonstrated experience with Data Product Management and establishing data product maintenance, best practices and governance frameworks. - Required:
Strong relationship-building skills with the ability to influence technical and non-technical stakeholders. - Required…
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