Hybrid (onsite 3x/week)

The Data Analyst supports the Operations Analytics team by ensuring that Zonar’s core business data is accurate, well-documented, and ready for reporting and AI-powered analytics. Working across source systems (Salesforce, Business Central, Staxbill, GTC), this role combines hands-on data analysis with data governance responsibilities profiling data quality, resolving inconsistencies, building documentation standards, and providing validated data sets that BI, Revenue, and cross-functional teams can trust. As Zonar launches its Data Readiness initiative, this analyst will play a central role in the discovery phase: mapping where key data live, assessing its quality, classifying data sets, and working with IT, Product, and Engineering teams to clean and govern it. This is a data-first role: the person who knows what data exists, how reliable it is, and what needs to happen before anyone builds a dashboard or trains a model on it.

Key Responsibilities and Duties:

• Analyze and profile data across Zonar’s core systems (Salesforce, Business Central, Staxbill, GTC) to assess completeness, accuracy, consistency, and timeliness.
• Write SQL queries to validate data, identify duplicates, detect anomalies, and compare source systems against the data warehouse and reporting outputs.
• Build and maintain data quality scorecards that give leadership visibility into the health of key data domains (customer, revenue, product, device).
• Perform ad-hoc analysis to support cross-functional teams with data requests, incident investigations, and customer health questions.
• Use AI-assisted tools (Claude, Lovable) to accelerate data profiling, anomaly detection, and pattern identification.
• Support the creation and enforcement of Zonar’s Data Governance policy, including data ownership definitions, change management rules, and quality thresholds.
• Build and maintain a centralized data dictionary documenting field definitions, source-of-truth assignments, data classifications (reference, operational, strategic), and transformation logic across platforms.
• Map data flows between systems: what data moves where, how it’s transformed, and what the expected behavior is at each integration point.
• Produce data lineage documentation showing how key metrics (MRR, churn, NPS, device health) are calculated from raw data through to dashboards.
• Track and log all data quality issues, cleanup activities, and governance decisions for audit and institutional knowledge.
• Lead the discovery phase of the Data Readiness initiative: inventory of what data exists across all business systems, where it lives, who owns it, and what condition it’s in.
• Coordinate with data owners across Sales, Finance, Operations, and Product to classify, remediate, and validate identified data issues.
• Support IT’s evaluation of the existing on-prem data warehouse vs. cloud options by providing data inventory, usage patterns, and storage analysis.
• Help define data retention policies based on business use cases and AI readiness requirements.
• Partner with the BI Analyst to ensure dashboards and reports consume clean, validated, and well-documented data sources.
• Support the Revenue Analyst with data validation for billing reconciliation, MRR calculations, and subscription lifecycle data.
• Provide structured exports and documentation so stakeholder teams can access data without introducing quality risks.
• Participate in the weekly Data Readiness working group, reporting on quality metrics, governance milestones, and remediation progress.

Knowledge, Skills, and Abilities:

• Bachelor’s degree in data analytics, business analytics, information systems, engineering, or a related field.
• 3+ years of experience in data analysis, data quality, business intelligence, or a related analytical role in a B2B, SaaS, or technology environment.

Technical Proficiency:

• SQL: Intermediate-Advanced skills writing queries (JOINs, GROUP BY, subqueries, window functions) for data validation and profiling.
• Excel: Advanced knowledge (Pivot Tables, VLOOKUP/INDEX-MATCH, data cleaning formulas, conditional formatting for audits).
• Data Quality: Can design validation rules, completeness checks, deduplication logic, and data quality scorecards.
• REST APIs & JSON: Can read API documentation, review JSON payloads, and understand data flows between systems.
• Documentation: Can create data dictionaries, field mapping specs, data lineage diagrams, and governance policies.

Soft Skills:

• Problem-Solving: Ability to dig into data to find root causes of quality issues, not just symptoms.
• Communication: Skill in translating data findings into clear summaries for both technical and non-technical stakeholders.
• Collaboration: Willingness to work closely with IT, Operations, Engineering, Sales, and Finance teams on data remediation.
• Attention to Detail: Meticulous approach to data validation — catches problems before they reach executive presentations.

Preferred (Plus)

• Experience supporting data governance or data readiness initiatives, especially in companies adopting AI/ML capabilities.
• Familiarity with data warehouse concepts (star schema, fact/dimension tables, ETL patterns).
• Experience in telematics, IoT, fleet management, or similar B2B SaaS industries.
• Familiarity with Claude Code, Supabase, or AI-assisted analytics tools.
• Exposure to data cataloging or metadata management practices.
• Experience with CRM platforms (Salesforce or HubSpot) and ERP systems (Business Central, NetSuite).
• Familiarity with concepts like Churn, NPS, MRR, or Customer Health.

Salary: 7M - 7.8M/monthly