VP Lead Data Engineer (Hybrid)

Bancorp Bank, The•Sioux Falls, SD

3d•Hybrid

About The Position

Leads enterprise data and implementation efforts to integrate customer, client, and transaction data into core reports across all business lines. Maps and translates raw data into structured formats that enhance reporting and user tool functionality. Drives enterprise data architecture, including the design and expansion of the Snowflake data model, to support scalable and standardized processor integrations. Establishes technology-driven oversight processes and leads processor launches, migrations, and system integrations to ensure end-to-end data integrity, compliance, and audit readiness. At The Bancorp, we’ve spent more than 25 years driving innovation in the financial services industry. As one of the first banks to embrace fintech, we combine technology, expertise and a forward-looking approach to deliver creative, real-world solutions. We work side by side with our partners to help them grow and innovate with confidence. Across Fintech Solutions, Institutional Banking, Commercial Lending and Real Estate Bridge Lending, we provide the people, processes, technology and banking capabilities that turn bold ideas into outcomes. Join a team that brings urgency and rigor to every challenge and plays a direct role in driving growth for our clients and the communities we serve.

Requirements

Undergraduate degree in a related field or an equivalent combination of training and experience.
10 or more years of experience in enterprise data integration, processor implementations, financial services data architecture, or related fields.

Nice To Haves

Master’s degree.
Strong working knowledge of credit or debit card issuing.
Excellent verbal, written, and interpersonal communication skills.
Team player, able to work effectively in a team fostered, multi-tasking environment.
Proficient in Microsoft Office suite, e.g., Excel, PowerPoint, Word, Outlook, SAS, SQL, BOBJ.
Experience leading enterprise data warehouse initiatives (e.g., Snowflake or comparable platforms).
Experience supporting AML/fraud monitoring systems such as Actimize or similar platforms.
Experience leading cross-functional processor implementations or large-scale platform migrations in a regulated financial environment.

Responsibilities

Manages teams responsible for reviewing, mapping, and analyzing data provided to the Bank from third parties.
Leads cross-functional implementation efforts across IT, Fraud, FCRM, Compliance, Audit, Operations, and processor partners to ensure successful data onboarding and system integration.
Establishes raw data requirements necessary to operate the bank’s programs compliantly and efficiently.
Interprets compliance regulations for systems and processes to ensure that fraud, risk, operational and compliance controls are in place, reports can be generated, and systems are in accordance with federal, state, and local rules and regulations for the products and industry.
Translates regulatory, fraud, AML, and operational requirements into enterprise data model specifications and scalable monitoring infrastructure.
Provides guidance to map and document data, i.e., new, and existing transaction codes, so system generated data can be categorized for use in research and reporting.
Reviews, audits, and revises the functional specifications documents related to field mapping.
Ensures that data is accurately mapped to processor fields, identify and correct errors as needed.
Disseminate the information to the appropriate teams.
Writes and tests procedures for new systems, systems elevations, and system changes.
Drafts rules, queries, and related process changes driven by new or existing automation and applications.
Communicates new procedures to affected internal parties.
Owns enterprise data governance documentation and implementation standards for new processors, platforms, and system changes.
Leads data and datasets used during system builds, enhancements, modifications, and mapping.
Develops business requirements and works closely with stakeholders to justify project proposals.
Owns data architecture strategy for new processor implementations and major platform migrations, including reconciliation validation, dual-processor transitions, and cutoff population documentation for audit defensibility.
Tests system and process changes to ensure accurate and efficient data entry, maintenance, and reporting.
Ensures workflow quality through structured testing and feedback.
Implements process improvements and enhancements for service delivery.
Reviews, audits, and revises functional specification documents related to the field mapping within the Actimize or other system(s).
Ensures data is mapped to the processor fields, identify and correct errors.
Leads integration of enterprise data model requirements into Actimize modernization initiatives (e.g., Actimize 2.0), ensuring monitoring scalability and reduction of processor-specific rework.
Creates business unit documentation, including a program parameterization tool mapping processor program IDs to parameters used to identify spend violations and forecast program activity.
Maintains authoritative program parameter and processor mapping frameworks supporting fraud detection, AML monitoring, compliance reporting, and operational forecasting.
Analyzes and integrates multi-technology data systems through a unified back-end platform and web-enabled front-end while owning data quality across data flows.
Designs and expands enterprise-scale data infrastructure (Snowflake and associated systems), enabling standardized ingestion patterns and accelerating future processor onboarding.
Defines common analytics frameworks and tools leveraged across the organization to drive innovation and experimentation.
Establishes enterprise data standards to reduce duplication, eliminate fragmented ETL processes, and improve reporting consistency across business lines.
Transforms data insights into actionable reports, targeting algorithms, and model features and conceptualize coding, deploying, and iterating on predictive analytic solution designs from prototypes to production systems.
Identifies practical approach to test and learns key hypotheses to extend analytic insight.
Establishes criteria for and executes on the creation of alerts and reports for business units with emphasis on Compliance and Fraud/ AML Monitoring teams.
Ensures enterprise-level data integrity supporting audit, regulatory examinations, CIP/KYC integrations, and cross-processor reconciliations.
Performs other duties as assigned.