Sr. Business Systems & Data Analyst; Enterprise Information

Arctiq is a global, intelligence-driven technology services company delivering professional and managed services across Hybrid Cloud Infrastructure, Networking & Connected Experiences, Cybersecurity, Data & AI, Autonomous Operations & Intelligence, and Enterprise Service Management. We help organizations operate, secure, and modernize complex environments by unifying infrastructure, networking, data, security, automation, and observability under a single, integrated operating model. Our work focuses on helping customers reduce operational friction, improve resilience, and make better, faster decisions as their environments evolve.

Arctiq builds on decades of industry expertise and a customer-centric ethos to deliver exceptional value to clients across diverse industries.

Department:
Strategic Initiatives

Reports To:

VP of Emerging Tech and Ops

The Business Systems & Data Analyst (Enterprise Information)

is an operational enforcement and monitoring role responsible for protecting the fidelity of information as it moves across the client's systems. The EIA acts as the standing owner of data health across every system. Enterprise:
Hub Spot CRM, the Association Management System (AMS), ERP and event platforms, the data warehouse, iPaaS and other integration layers, and other hosted and Saas member-facing digital platforms.

This person ensures that the right data lives in the right system, that integrations behave as designed, that system ownership is documented and measurable, and that anomalies, conflicts, and integrity failures are identified, escalated, and resolved.

• 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 elevate 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.
• Participate in integration design and implementation reviews to ensure governance standards are embedded before go-live, not retrofitted after.
• 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 work streams 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 Hub Spot 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.

• 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…