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 — from ingestion into Snowflake to downstream delivery into Oracle, reporting platforms, and other systems. This role serves as a critical bridge between the Data Engineering team and its key business partners in Finance and Premium Operations, translating business needs into data requirements and translating data findings into clear, actionable business insight.
Because this role sits at the intersection of engineering and business, exceptional communication skills are essential. The Senior Data Analyst must be equally comfortable working through a technical data problem with an engineer and presenting a reconciliation finding to a Finance or Operations leader, translating clearly in both directions.
Minimum Qualifications
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.
Primary Job Functions
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.
The above cited duties and responsibilities describe the general nature and level of work performed by people assigned to the job. They are not intended to be an exhaustive list of all the duties and responsibilities that an incumbent may be expected or asked to perform.
Skills and Competencies
Communication & Collaboration — Critical for This Role
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.
Full benefit package including medical, dental, life, vision, company paid short/long term disability, 401(k), tuition assistance and more.
FORTEGRA IS NOT ACCEPTING UNSOLICITED RESUMES FROM SEARCH FIRMS FOR THIS POSITION.
Applicants must be authorized to work for any employer in the United States. We are unable to sponsor or assume sponsorship of employment visas now or in the future. We welcome applicants of all backgrounds and national origins.
Fortegra has recently been made aware of unauthorized communications regarding career opportunities by individuals not associated with Fortegra or our recruitment team. Fortegra will only contact you from the Fortegra domain address (fortegra.com). If you receive a message from someone posing as a Fortegra recruiter via text message, WhatsApp, Telegram or other messaging platform, please report it as phishing and block the sender.
Internal Notice: As part of our commitment to talent development, this position is open for internal promotion applications at the time of public posting.
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