Senior Data Analyst

About the role

The Senior Data Analyst is a member of the Data Engineering team, responsible for acquiring, managing, validating, and analyzing data as it moves through Fortegra's data ecosystem.

Responsibilities

• Data Validation & Quality
• Perform data validation at both the intake (Snowflake ingestion) and output (downstream delivery) stages to ensure accuracy, completeness, and integrity.
• Develop and execute data quality checks, reconciliation routines, and exception reports to identify and resolve discrepancies.
• Serve as the data quality owner for assigned data domains; document findings and partner with Data Engineering to resolve root causes.
• Validate bordereau data received from MGAs/Program Administrators against expected schemas, field requirements, and business rules.
• Analysis & Reporting
• Design, build, and maintain multi-layered dashboards, KPI reports, and ad-hoc analyses to support Finance, Operations, and Leadership.
• Perform quantitative and statistical analysis to surface trends, anomalies, and business insights.
• Generate and automate recurring reports, reducing manual effort and improving timeliness of information delivery.
• Fulfill ad-hoc reporting requests from Finance, Underwriting, Actuarial, and other stakeholders.
• Contribute to monthly, quarterly, and annual financial close processes by validating data and producing supporting schedules.
• Data Engineering Collaboration
• Partner closely with Data Engineers to define, test, and validate data pipelines — providing business context and analytical perspective that engineers may not have.
• Develop and maintain SQL scripts and stored procedures for data extraction, transformation, and transmission between systems (e.g., Snowflake to Oracle).
• Participate in requirements gathering and UAT for new data integrations, system enhancements, and reporting solutions.
• Understand system capabilities across Snowflake, Oracle EBS, and reporting platforms to design queries and outputs optimized for performance and usability.
• Stakeholder & Business Relationship Management
• Build and maintain positive working relationships with internal customers in Finance, Premium Operations, Underwriting, IT, and Actuarial.
• Translate business requirements into technical specifications and communicate findings clearly to both technical and non-technical audiences.
• Capture customer requirements and agree on service-level expectations for recurring deliverables.
• Handle escalations, assess data or reporting issues, and implement corrective action as needed.
• Identify opportunities for process improvement and automation; document current-state processes and propose enhanced workflows.
• Documentation & Governance
• Document own work thoroughly — including technical specifications, data dictionaries, process flows, and business requirements.
• Maintain accurate records of all data sources, transformation logic, validation rules, and reporting outputs.
• Support internal and external audits by providing clear data lineage and documentation.

Requirements

• Education
• Bachelor's degree in Accounting, Statistics, Finance, Computer Science, Data Science, Information Management, or a related field — or equivalent professional experience.
• Experience
• 3–7 years of experience in data analytics, business analysis, or a related discipline, preferably in financial services or insurance.
• Demonstrated experience working with structured databases and large datasets from multiple sources.
• Experience with data warehousing platforms, specifically Snowflake (strongly preferred).
• Experience with data presentation and BI tools such as Microsoft Power BI, Oracle OBIEE/OAC, or equivalent.
• Familiarity with Oracle EBS or similar ERP/financial systems is a plus.
• Experience with insurance bordereau processing, premium operations, or financial close processes is advantageous.

Qualifications

• Advanced SQL skills required; experience with Python or another scripting language is a plus.
• Proficiency with Snowflake (queries, warehousing concepts, data sharing) strongly preferred.
• Strong knowledge of data modeling, data mining techniques, and ETL/ELT concepts.
• Knowledge of accounting, financial reporting, and/or insurance processes and terminology.
• Exceptional analytical and critical thinking skills; ability to work with large, complex datasets from multiple sources.
• Proficiency with MS Office suite (Excel, Word, Outlook, PowerPoint); experience with BI tools such as Power BI or Oracle OAC.

Skills And Competencies

• Communication & Collaboration
• This role is the connective tissue between Data Engineering and the business. The ability to communicate clearly, listen carefully, and build trust with both technical and non-technical partners is not a soft skill here — it is a core job requirement.
• Ability to translate complex data findings into plain language for Finance, Operations, and executive audiences.
• Ability to translate business requirements into clear, actionable technical specifications for Data Engineering.
• Strong written communication skills for documentation, requirements gathering, status reporting, and escalations.
• Comfort facilitating working sessions, presenting analyses, and leading discussions with cross-functional stakeholders.
• Relationship-building instinct — proactively engages partners in Finance and Premium Operations rather than waiting to be asked.
• Technical Skills
• Advanced SQL skills required; experience with Python or another scripting language is a plus.
• Proficiency with Snowflake (queries, warehousing concepts, data sharing) strongly preferred.
• Strong knowledge of data modeling, data mining techniques, and ETL/ELT concepts.
• Knowledge of accounting, financial reporting, and/or insurance processes and terminology.
• Exceptional analytical and critical thinking skills; ability to work with large, complex datasets from multiple sources.
• Proficiency with MS Office suite (Excel, Word, Outlook, PowerPoint); experience with BI tools such as Power BI or Oracle OAC.
• Professional Competencies
• Organizational skills and ability to manage multiple priorities and deadlines simultaneously.
• Lean/continuous improvement mindset — focused on building scalable, efficient, and repeatable processes.
• High attention to detail and accountability for data accuracy and quality.
• Collaborative team player who operates well within a technical team while serving business partners effectively.

Benefits

Full benefit package including medical, dental, life, vision, company paid short/long term disability, 401(k), tuition assistance and more.

Pay

TBD

Schedule

TBD