Data Analytics Analyst 4

The Reporting Support Analyst is responsible for the reliability, accuracy, usability, and operational support of enterprise reporting solutions developed and delivered through Power BI. The analyst serves as the initial point of contact for report questions, production incidents, data discrepancies, refresh and access concerns, and business process inquiries. The role bridges business operations and technical delivery teams by investigating issues, validating data and Power BI report behavior, coordinating resolution activities, documenting outcomes, and communicating status to stakeholders.

The Reporting Support Analyst is expected to investigate deeply, validate data, coordinate response, and define a clear technical handoff. The role is not the primary owner for complex data-pipeline engineering, application development, enterprise platform administration, or final product-prioritization decisions. Those activities remain with the appropriate Data Engineering, CDP, Reporting Development, platform, security, or product-management teams. The analyst remains accountable for support coordination, business validation, evidence, communication, and confirmed closure.

Databricks is a cornerstone technology for the broader Reporting and CDP organization. The analyst must be able to use Databricks and SQL to investigate data, trace source-to-report flows, validate transformations, recognize pipeline or data-quality issues, and partner effectively with Data Engineering and development teams. The role does not require full data-engineering ownership, but it does require hands-on platform fluency and the ability to distinguish business, data, report, security, configuration, and technical defects.

Serve as the first line of support for reporting incidents, data questions, access issues, and report usage inquiries. Monitor reporting operations and identify failures, delays, incomplete outputs, or service disruptions. Validate scheduled report execution, output availability, publication, and restoration following an incident. Escalate technical defects with a clear problem statement, business impact, evidence, and steps already completed. Confirm resolution through business validation, production verification, and documented closure criteria.

Navigate Databricks workspaces and use Databricks SQL to investigate data anomalies and reporting discrepancies. Trace data from source and ingestion through curated data products and reporting consumption layers. Validate transformations, business rules, filters, joins, aggregations, and source-to-target results. Review notebook, job, or pipeline results needed to determine whether an issue is caused by latency, failed processing, data quality, transformation logic, or downstream reporting. Use data lineage and catalog information, including Unity Catalog where applicable, to identify relevant tables, views, owners, and downstream dependencies. Partner with Data Engineering, CDP, and Reporting Development to support root-cause analysis, testing, release validation, and post-deployment monitoring.

Perform SQL-based analysis, reconciliation, and expected-versus-actual validation. Determine whether an issue is related to source data, Databricks processing, CDP, report logic, security, configuration, distribution, or user interpretation. Interpret report calculations, parameters, filters, and business rules. Document findings, supporting evidence, decisions, and recommended actions in a form usable by both business and technical teams.

Triage requests, assess operational and compliance impact, assign appropriate priority, and coordinate ownership. Organize response activities across analysts, developers, data engineers, platform teams, and business subject-matter experts. Provide concise, timely status updates that explain impact, current findings, ownership, next actions, and known workarounds. Participate in root-cause reviews and convert lessons learned into monitoring, documentation, or process improvements. Maintain complete and accurate ticket records through resolution and closure.

Help users identify the appropriate report or data product for an operational need. Explain report behavior, calculations, data definitions, refresh timing, known limitations, and expected results in business-friendly language. Support training, adoption, and change communications for reporting solutions. Manage expectations professionally during incidents, competing priorities, and unresolved investigations.

Support Power BI reports, paginated reports, dashboards, refreshes, parameters, subscriptions, rendering, and basic access troubleshooting. Validate scheduled-job execution and coordinate recovery or rerun activities through established operating procedures. Support release readiness, production deployment validation, and stabilization monitoring.

Follow established SOX 404 control procedures, evidence requirements, documentation standards, and escalation protocols. Support audit inquiries and maintain evidence demonstrating completed monitoring, validation, recovery, and control activities. Create and maintain runbooks, knowledge articles, troubleshooting guides, report metadata, support procedures, and known-issue documentation. Promote cross-training, backup coverage, repeatable processes, and reduced dependence on individual subject-matter experts. Contribute to reporting standards, service metrics, trend analysis, and continuous improvement.

Bachelor's degree in Information Systems, Data Analytics, Computer Science, Business Analytics, Business Administration, or a related field, or an equivalent combination of education and relevant experience. Experience supporting business intelligence, reporting, data, analytics, or production operations in an enterprise environment. Hands-on experience writing and interpreting SQL for investigation, validation, and reconciliation. Working experience with Databricks or a comparable cloud data and analytics platform. Experience with Power BI or a comparable enterprise business intelligence platform. Demonstrated ability to communicate technical findings clearly to business and leadership audiences.

Hands-on experience supporting Power BI reports, dashboards, paginated reports, semantic models, refresh schedules, subscriptions, access, and production issue resolution. Experience validating report calculations, filters, parameters, data relationships, and source-to-report results to identify reporting defects and data discrepancies. Experience with Microsoft Fabric, data warehouses, enterprise semantic models, or related analytics platforms. Databricks SQL, Delta Lake, data lineage, or lakehouse concepts. Autosys or comparable enterprise scheduling and job-monitoring experience. Remedy Helix, ServiceNow, Jira, or comparable ticketing and work-management experience. SharePoint and enterprise knowledge-management experience. Experience supporting regulatory, financial, or SOX-controlled reporting. Utility, customer operations, billing, payments, field operations, or other relevant business-process knowledge.

Ownership and accountability: Drives issues through validation and closure rather than stopping at handoff. Analytical problem solving: Uses evidence to isolate the problem and distinguish symptoms from root causes. Customer focus: Supports users with patience, clarity, and appropriate urgency. Communication: Tailors technical depth for business users, developers, data engineers, and leaders. Collaboration: Works effectively across Reporting, CDP, Data Engineering, compliance, and business teams. Adaptability: Learns evolving data platforms, reports, business rules, and support processes. Risk awareness: Recognizes operational, data-quality, security, and compliance implications and escalates appropriately. Knowledge sharing: Documents repeatable solutions and actively builds team capability and backup coverage.

Timely, accurate triage and resolution of reporting support requests. High-quality incident records, investigation evidence, and stakeholder communications. Accurate identification of whether issues originate in source systems, CDP, reporting logic, security, configuration, distribution, or user interpretation. Reliable production validation following changes, reruns, fixes, and deployments. Reduction in repeat incidents through root-cause action, monitoring, and knowledge documentation. Consistent execution of compliance controls and evidence requirements. Improved organizational resiliency through cross-training, runbooks, and reduced key-person dependency. Trusted partnership with business customers and technical delivery teams.







Key Skills

Python | R | SQL | Data Visualization | Matplotlib | Seaborn | Tableau | Data Analysis | Data Integration | ETL Processes | Data Extraction | Data Transformation | Data Loading | Database Management | Statistical Analysis | Hypothesis Testing | Machine Learning | Predictive Modeling | Data Insights