We are working with a client to hire a Senior Enterprise Data Analyst to support enterprise data initiatives across finance, underwriting, actuarial, and operational systems. This role sits at the intersection of data governance, reconciliation, transformation, automation, and advanced analytics. The Senior Enterprise Data Analyst plays a critical role in improving data integrity, supporting core system implementations (Workday, Salesforce), enhancing enterprise data warehouse capabilities, and enabling data-informed decision-making across the organization. As a Senior Enterprise Data Analyst, you will serve as a subject matter expert in data transformation, reconciliation, and enterprise analytics.
- This role is based in Austin, TX and operates within a hybrid work model and base is $110k-$130k base (range varies based on level of skillset) plus bonus and full benefits.
Responsibilities:
- Data Transformation & Integration: Collect, cleanse, and transform complex insurance datasets, including premium, claims, endorsements, billing, and policy lifecycle data. Align external MGA data structures with Incline’s internal systems and enterprise warehouse architecture. Validate and standardize data mappings across Duck Creek Reinsurance, Workday, Salesforce, and Snowflake environments. Improve data pipeline accuracy and consistency across systems.
- Data Integrity, Reconciliation & Governance: Investigate and resolve complex data discrepancies across Snowflake, Oracle, and reporting platforms. Perform root cause analysis on mapping, allocation, premium, and financial reconciliation issues. Support regulatory reporting, Schedule F workflows, treaty reporting, and financial reconciliation processes. Maintain strong data quality standards and governance documentation. Proactively monitor data pipelines to identify and correct inconsistencies.
- Enterprise Data Warehouse & Modeling: Design and optimize data models to support efficient querying and robust storage within Snowflake. Develop advanced SQL queries and transformation logic. Contribute to metadata documentation and warehouse best practices. Support scalable data architecture improvements.
- Analytics & Reporting: Conduct in-depth analysis to identify trends, anomalies, and operational improvement opportunities. Develop executive-ready dashboards and reporting solutions (Power BI, Quick Sight, or similar tools). Support underwriting performance analysis, claims trends, portfolio profitability, and financial analytics. Translate business requirements into structured reporting logic and data models.
- Automation & Advanced Analytics: Identify manual processes and design automation solutions using SQL and Python. Develop scalable scripts to streamline reconciliation, validation, and reporting workflows. Explore predictive modeling, anomaly detection, and AI-supported insights where applicable. Support user acceptance testing (UAT) and enterprise system implementations.
- Cross-Functional Partnership: Act as a key liaison between IT, Actuarial, Finance, Underwriting, and Operations. Partner with stakeholders to define and refine business metrics and reporting standards. Provide technical guidance to junior analysts when needed. Independently manage complex data initiatives from problem identification through resolution.
Required Qualifications:
- Experience: 5+ years of experience in data analysis, enterprise data operations, or analytics roles. Strong experience working with complex insurance datasets (policy, claims, billing, endorsements).
- Education: Bachelor’s degree in Data Science, Computer Science, Information Systems, Mathematics, Statistics, or related field. Master’s degree preferred.
- Technical Expertise: Advanced SQL proficiency. Strong Python programming skills. Experience with ETL tools such as Matillion, DBT, or similar platforms. Deep understanding of data modeling and insurance-focused database design. Experience with Snowflake and cloud-based data environments (AWS preferred). Familiarity with JSON, XML, and modern data interchange formats.
- Core Competencies: Strong analytical reasoning and problem-solving skills. Ability to translate complex technical findings into clear, actionable insights. Strong communication and collaboration skills across technical and business teams. High level of ownership and attention to detail
If you meet the required qualifications and are interested in this role, please apply today.
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