Sr. Business Systems & Data Analyst (Enterprise Information)

Key Responsibilities

• Monitor data quality, completeness, consistency, and accuracy across all enterprise systems on a continuous basis.
• Maintain a data health scorecard by system and domain, updated on a defined cadence.
• Identify anomalies, duplicates, orphaned records, broken mappings, and integration failures across CRM, AMS, ERP, data warehouse, and digital platforms.
• Enforce data standards and governance policies set by the organization.
• Flag and escalate non-compliant data, failed integrations, or system changes that violate established standards.
• Track, support and maintain resolution of escalated issues through to closure via Service Desk.
• Maintain the enterprise system-of-record registry: for every data domain, document which system is authoritative, which systems consume the data, and which teams are accountable.
• Track and publish the accountability matrix for data quality by system owner, updated as personnel or system scope changes.
• Quantify system ownership gaps — domains without a named owner, systems without defined stewards, integration points without documented accountability.
• Support system owners in understanding their data quality obligations under current governance policy; this role does not set those obligations but ensures they are understood and met.
• Maintain a living inventory of enterprise systems, integration points, APIs, and data flows as the architecture evolves during the active build-out period.
• Monitor integration health across iPaaS workflows, API connections, ETL processes, and data warehouse pipelines.
• Validate that data written by integrations lands in the correct system of record, in the correct format, and at the expected frequency.
• Identify and document integration failures, transformation errors, field mapping drift, and synchronization gaps.
• Coordinate with integration partners and technical teams during incident resolution; the EIA owns the issue log and drives it to closure.
• Participate in all SDLC and project workstreams where data is created, changed, migrated, integrated, or retired.
• Review solution designs, data mapping documents, field definitions, and acceptance criteria for compliance with current governance standards.
• Flag governance gaps, source-of-record violations, and integration risks to the project team and leadership before go-live.
• Ensure that new system implementations, including the active HubSpot rollout and any AMS, ERP, or data warehouse integrations, adhere to established data standards from the first configuration decision.
• Document data decisions made during projects; maintain a decision log that prevents future teams from re-litigating resolved questions.

Metrics, Reporting, and Executive Communication

• Deliver a recurring data integrity status report summarizing system health, escalated issues, trends, and recommendations.
• Translate technical data quality findings into plain-language summaries that system owners and business stakeholders can act on.
• Maintain audit-ready documentation of data quality metrics, issue history, escalation records, and resolution outcomes.
• Data quality monitoring – Identify, measure, and track integrity failures across domains and systems.
• System-of-record management – Maintain authoritative source registry; identify ownership gaps and conflicts.
• Integration oversight – Monitor API, ETL, and iPaaS health; validate field mapping and data movement.
• Metrics and scorecards – Produce and maintain data health dashboards and recurring status reports.
• Enterprise systems literacy – Understand CRM, AMS, ERP, warehouse, and digital platform data structures.
• SDLC participation – Review designs and acceptance criteria for governance compliance before go-live.
• Issue and escalation management – Log, track, escalate, and drive resolution of data integrity violations via Service Desk.
• Executive communication – Translate technical findings into business-language summaries and decision briefs.

Required Qualifications

• Bachelor’s degree in information systems, business analytics, data management, computer science, or a related field.
• Minimum 3 years of experience in data quality, data operations, systems administration, integration monitoring, or a closely related discipline.
• Demonstrated experience monitoring and validating data across multiple enterprise systems simultaneously.
• Working knowledge of CRM, AMS, ERP, data warehouse, and integration platform concepts and architectures.
• Ability to read and interpret integration payloads, API documentation, ETL mapping documents, and data flow diagrams.
• Experience producing data quality metrics, scorecards, or health reporting for operational and leadership audiences.
• Clear written and verbal communication skills across technical, operational, and executive audiences.
• Experience in HubSpot, Salesforce, Microsoft Dynamics or other cloud-based CRM administration and/or data management.
• Familiarity with AMS platforms or comparable association management systems.
• Exposure to data warehouse environments including Snowflake, Datadog, Databricks, Microsoft Fabric, Azure Synapse, or Power BI or other open-source semantic models.
• Experience with iPaaS platforms such as MuleSoft, Boomi, Workato, n8n, Azure, or other open-source Integration Services.
• Background in or exposure to data governance frameworks such as DAMA, DMBOK, DCAM or other data foundation and management layers — not as a designer but as an operator.
• Experience working inside an active system implementation or enterprise architecture build-out.
• Exposure to SQL or equivalent query tools sufficient to validate data and investigate anomalies independently.
• Exposure to Unix, Linux, or open-source tooling in a data operations or systems administration context.