Data Quality Analyst

Are you a Data Quality professional with strengths in finding and fixing data errors in critical Insurance systems? Global insurance leader is looking for a Lead Data Quality Engineer/Project Manager with strong experience exploring & summarizing ‘raw’ data sets using Structured Query Language (SQL), as well as the ability draw insights from existing data quality reports & dashboards. This position offers many opportunities for advancement, competitive compensation, offers some of the best benefits and 401k plan compared to any other company in the country and has a great reputation.

Employee testimonials:

• Outstanding group of professionals
• Excellent benefits including a fantastic 401K match
• Great flexibility to manage work life balance
• Employees go above and beyond to support each other and achieve objectives

Title: Lead Data Quality Engineer/Project Manager (Hybrid)

Location: Stamford, CT, Morristown, NJ, Manhattan, NY

Salary: $110,000 – $130,000 +Bonus

Responsibilities:

• Global insurance corporation is looking to hire a Lead Data Quality Engineer/Project Manager that will work closely with senior stakeholders to understand Data Quality issues and then liaise with Data & Analytics teams to drive technical data quality solutions.
• This position is responsible for finding & fixing data errors in our systems after they occur with SQL data quality validation rules and Power BI dashboards to track quality levels and drive remediation efforts.
• You will also work with Operations and IT teams, to implement “data quality by design” across various source systems & processes, to prevent manual data quality errors from occurring in the first place (e.g. working with IT to replace an optional free text field, with a mandatory drop down list of choices on their a core policy administration system).
• The ideal candidate will have several years of experience working in commercial insurance with some experience working with insurance administration systems (e.g. Genius, Frame, Wins, XLGC, etc.), demonstrating strong knowledge of commercial insurance processes across multiple functions (e.g., Underwriting, Claims, Operations, Finance) including how data flows from one department to another, ideally with a network of contacts across these multiple business functions.
• You will use your understanding of the challenges involved in capturing high quality data in the commercial insurance industry to drive improvements to systems and processes that will enhance data quality. Curiosity, attention to detail, a desire to get it right first time, ability to join the dots across people/processes/systems, and a proven track record in connecting teams and managing change projects will be essential to your success.
• You will use your SQL Coding Skills to Identify Root Causes to select, join, extract and compare various data records to explore the root cause of high level data quality issues highlighted in the master Data Quality Dashboard (DQD).
• You will work with Underwriting, Actuarial, Claims, Operations departments to understand the flow of data through the organization, identifying data quality ‘pain points’ and improvements to process and systems.
• You will manage projects end-to-end, leveraging virtual teams of internal experts, and contractors to deliver data quality improvements at scale through source system enhancements

Requirements:

• Strong quantitative data analysis skills including the ability to explore & summarize ‘raw’ data sets using Structured Query Language (SQL), as well as the ability draw insights from existing data quality reports & dashboards
• Experience in commercial insurance including direct experience working across multiple systems.
• Experience working with Commercial insurance systems (e.g., policy systems, claims systems, etc.)
• Strong project management skills to define & drive technology process improvement projects leveraging virtual teams to deliver permanent data quality improvements to data capture systems
• Strong networking skills, with a wide array of relevant stakeholder relationships already in place across multiple business functions and source systems
• Formal process improvement qualifications (e.g. Lean / Six Sigma) desirable to drive data quality enhancements through best practice process improvements to data capture systems
• Experience of user-centered design thinking (e.g. Agile sprints, discovery interviews, journey mapping) desirable to understand data capture systems & processes from a user perspective
• Certified Data Management Professional (CDMP) desirable