Business Data Analyst

ExlService Holdings Inc
  • Jersey City, NJ
  • $100,000–$140,000 Per Year
3 days ago

Job Description

We are seeking a Business Data Analyst with a strong background in large-scale data applications, data analysis, and transformation to support enterprise-level initiatives in the Property & Casualty (P&C) Insurance domain. The ideal candidate will bring hands-on expertise in SQL, data mapping, and business analysis, along with deep domain knowledge of policy and claims data. This role requires close collaboration with business stakeholders, SMEs, and technical teams to drive data accuracy, consistency, and value.

Base Compensation Range: 100,000 - 140,000

The posted range is the hiring range for this role - a subset of the broader range available to employees over time - and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate''s skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits

bachelors in related field

Key Responsibilities:

  • Perform end-to-end data analysis, including data profiling, validation, and transformation for large-scale data integration and reporting projects.
  • Develop source-to-target data mappings (STTM) and documentation based on business requirements.
  • Collaborate with business users and stakeholders to gather, analyze, and translate functional requirements into technical specifications.
  • Work with data engineers and developers to implement and validate data consolidation, standardization, and transformation logic.
  • Optimize complex SQL queries for performance and accuracy in handling large datasets.
  • Participate in data quality assessments and recommend data cleansing or enrichment strategies.
  • Leverage domain knowledge of Property & Casualty Insurance-including policy administration and claims lifecycle-to ensure data alignment with business processes.
  • Facilitate communication between business SMEs, data modelers, and technical teams for successful data delivery and adoption.

Required Skills & Experience:

  • 5+ years of hands-on experience in data analysis, data mapping, and data transformation within enterprise data environments.
  • Strong proficiency in SQL, including analytical functions, query optimization, and performance tuning.
  • Proven experience developing source-to-target mapping (STTM) documents and understanding ETL/data flow processes.
  • Exposure to data consolidation, standardization, and transformation across heterogeneous data sources.
  • In-depth knowledge of the Property & Casualty Insurance domain,
  • Exceptional communication and interpersonal skills-able to work effectively with technical teams, business stakeholders, and subject matter experts.
  • Strong documentation skills with the ability to create clear and concise technical and business artifacts.

Key Responsibilities:

  • Perform end-to-end data analysis, including data profiling, validation, and transformation for large-scale data integration and reporting projects.
  • Develop source-to-target data mappings (STTM) and documentation based on business requirements.
  • Collaborate with business users and stakeholders to gather, analyze, and translate functional requirements into technical specifications.
  • Work with data engineers and developers to implement and validate data consolidation, standardization, and transformation logic.
  • Optimize complex SQL queries for performance and accuracy in handling large datasets.
  • Participate in data quality assessments and recommend data cleansing or enrichment strategies.
  • Leverage domain knowledge of Property & Casualty Insurance-including policy administration and claims lifecycle-to ensure data alignment with business processes.
  • Facilitate communication between business SMEs, data modelers, and technical teams for successful data delivery and adoption.

Required Skills & Experience:

  • 5+ years of hands-on experience in data analysis, data mapping, and data transformation within enterprise data environments.
  • Strong proficiency in SQL, including analytical functions, query optimization, and performance tuning.
  • Proven experience developing source-to-target mapping (STTM) documents and understanding ETL/data flow processes.
  • Exposure to data consolidation, standardization, and transformation across heterogeneous data sources.
  • In-depth knowledge of the Property & Casualty Insurance domain,
  • Exceptional communication and interpersonal skills-able to work effectively with technical teams, business stakeholders, and subject matter experts.
  • Strong documentation skills with the ability to create clear and concise technical and business artifacts.

Numbers & Facts

LocationJersey City, NJ
Salary$100,000–$140,000 Per Year

Skills

  • Business Analysisunmatched
  • Business Processesunmatched
  • Communication Skillsunmatched
  • Data Analysisunmatched
  • Data Mappingunmatched
  • Data Modelingunmatched
  • Data Profilingunmatched
  • Data Qualityunmatched
  • Data Setsunmatched
  • Database Extract Transform and Load (ETL)unmatched
  • Documentationunmatched
  • Functional Analysisunmatched
  • Insuranceunmatched
  • Interpersonal Skillsunmatched
  • Performance Tuning/Optimizationunmatched
  • Policy Developmentunmatched
  • Process Flowunmatched
  • Property and Casualty Insuranceunmatched
  • Query Analysisunmatched
  • Query Optimizationunmatched
  • Requirements Managementunmatched
  • SQL (Structured Query Language)unmatched
  • Team Playerunmatched

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