Department: Enterprise Analytics
Reports to: Chief Data Analytics Officer
Status: Exempt/ Officer
Grade: 13
Salary Range: $96,089 - $177,069
Salary range updated 4/10/2026. Actual compensation within the pay range will be determined based on factors including, but not limited to, skills, prior relevant experience, and specific work location.
Location: MA, NY, CT, RI, VT
Principal ObjectiveThe Data Integration & Reporting Officer is responsible for enterprise data integration, data standardization, and trusted analytics capabilities across the organization. This role owns the strategy, standards, and delivery of scalable data solutions, integration of current and legacy data sources, and development of a reliable data foundation for analytics, AI, and management decision-making. The position plays a key role in data standardization, enterprise reporting transformation, and continuous improvement of analytics capabilities. Works closely with Technology, Finance, Risk, Operations, and business lines leaders
Key Accountabilities:Enterprise Data Integration, Standardization & Quality- Lead integration and standardization of data from multiple source systems into the enterprise data platform, including Snowflake.
- Direct onboarding of historical and legacy data sources, including Jack Henry / jhaKnow, into governed reporting environments.
- Oversee resolution of data variances impacting management reporting, operational reporting, or analytics.
- Promote consistent, trusted, and scalable data assets across the organization.
Data Transformation & Reporting Architecture- Lead design and governance of SQL views, curated datasets, and reporting structures that convert raw data into usable business information.
- Ensure reporting structures align to key business dimensions such as region, officer, product, department, relationship, and customer.
- Improve consistency, usability, and performance of enterprise reporting assets.
- Define standards for approved and controlled reporting datasets.
Data Conversion & Strategic Change Initiatives- Lead conversion of critical data elements from legacy Jack Henry / jhaKnow structures into FIS reporting and enterprise data structures.
- Oversee mapping, transformation, and reconciliation of data between Jack Henry, FIS, and enterprise reporting platforms.
- Direct integration of legacy and current data sources into unified reporting views.
- Identify and resolve inconsistencies affecting trend analysis, management reporting, or strategic decision-making.
AI & Advanced Analytics Data Foundation- Establish and strengthen the trusted data foundation required for AI, machine learning, and advanced analytics use cases.
- Ensure availability of clean, governed, and well-documented datasets for model development, experimentation, and future intelligent solutions.
- Improve traceability, consistency, and reliability of data supporting advanced analytics initiatives.
- Partner with analytics and technology teams to enable scalable AI readiness.
Governance, Controls & Leadership- Maintain governance standards for data mapping, transformation, and validation.
- Support data governance, lineage, transparency, and audit readiness requirements.
- Promote use of approved, controlled, and standardized reporting source across the enterprise.
Education:- Bachelor's degree in a relevant field; advanced degree preferred.
Experience:- 5-7+ years of experience in enterprise data integration, reporting, analytics, or data warehousing environments.
- Strong experience with SQL Server, SQL development, relational databases, and enterprise reporting environments.
- Experience with enterprise data platforms such as Snowflake or similar cloud-based data warehouse technologies preferred.
- Experience integrating data from multiple source systems, including banking, loan, deposit, customer, or financial reporting platforms preferred.
- Experience with Jack Henry / jhaKnow, FIS, or similar banking and reporting platforms preferred.
- Experience working with data quality, reconciliation, validation, and standardized reporting processes.
- Ability to work cross-functionally with Technology, Finance, Risk, Operations, and business stakeholders.
Skills & Knowledge:- Strong background in data integration, reporting architecture, reconciliation, and data quality management.
- Proven ability to lead enterprise initiatives and cross-functional delivery.
- Strong communication, leadership, problem-solving, and organizational skills.
