Business Analyst

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. 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.Location: HYBRID Alexandria, VA Department: Strategic Initiatives Reports To: VP of Emerging Tech and OpsThe 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: HubSpot 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.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 standardsTrack, support and maintain resolution of escalated issues through to closure via Service DeskMaintain 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 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.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 outcomesData 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.Soft SkillsOperational vigilance: notices when something is wrong before anyone else does and acts without being asked.Accountability orientation: believes data ownership is not optional and pursues resolution with persistence and professionalism.Structured thinking: works from evidence, builds a log, tracks trends — does not rely on memory or informal observation.Business fluency: understands why the data matters to the organization, not just what is technically wrong with it.Diplomatic firmness: can tell a system owner their data is broken, document the conversation, and escalate if it isn't fixed — without damaging the working relationship.Comfort in ambiguity arrives while systems are being built; can operate without a complete map and help create one as the landscape stabilizes.Stakeholder Coordination:Work directly with system owners, business stakeholders, and technical teams to resolve data quality issues, ownership gaps, and integration failures.Facilitate working sessions when definition conflicts, source-of-record disagreements, or integration failures require cross-functional resolution.Communicate enforcement actions and escalation decisions clearly and professionallySupport governance committees by providing data health metrics, issue status, and trend analysis; does not create or modify governance policy.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.Familiarity with 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.Working Conditions:Full-time onsite role with onsite and remote collaboration.Occasional travel may be required for key partner engagements, pilots, or major program milestones.Regular coordination across multiple time zones with internal teams and external partners as