Data Analyst

Responsibilities

• Support production jobs, perform data validation, design ad-hoc scripts, programs, ETL pipelines, and implement small production fixes while ensuring data quality, reliability, and alignment with enterprise data standards.
• Work on a hybrid schedule from our New York office.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Finance, or a related field.
• 5+ years of experience in the Insurance domain, preferably within Brokerage or P&C.
• Strong understanding of Data Warehousing, Data Lakehouse, and Master Data Management (MDM).
• Hands-on experience supporting production environments on Azure Cloud with SQL Server.
• Advanced proficiency in SQL (complex queries, joins, stored procedures, indexing).
• Strong hands-on experience with Python.
• Experience with ETL tools such as ADF, SSIS, Informatica, or DataStage.
• Proficient in MS Excel for data analysis and validation (Pivot Tables, Power Pivot).
• Experience using BI reporting tools for data validation and reconciliation.
• Ability to work independently and deliver results in a fast-paced environment.
• Hands on experience with API integration.
• Hands on experience with version control systems - GitHub.

Qualifications

• Strong hands-on experience with Azure Data Factory (ADF).
• Advanced proficiency in SQL Server.
• Experience with BI reporting tools (Power BI, SSRS, Tableau, or similar).
• Experience with Master Data Management (MDM) initiatives.

Skills

• Data Warehouse principles, including fact/dimension modeling, historical data management, reconciliations, and data conversions.
• Statistical techniques and exploration data analysis using tools such as Python, SQL, or Excel.
• Source-to-target reconciliation.
• Operational and business validation checks.
• Design and develop ad-hoc ETL processes using ADF and Python for analytics, fixes, and enhancements as part of production support activities.
• Monitoring production jobs, troubleshooting failures, and performing root cause analysis daily.
• Create and maintain technical and functional documentation (requirements, design, process flows).
• Identify opportunities to improve data processes and analytics solutions using technology.
• Deliver high-quality analytical outputs and visual storytelling to support management decision-making.
• Collaborate with cross-functional teams, including senior engineers, analysts, and business stakeholders, to support enterprise data initiatives.

Benefits

• Comprehensive health care coverage.
• A 401k plan.
• Tuition reimbursement.