2026-7980 Data QA Engineer-Mid (Mid Shift)

AGSI was incorporated in April 2016. We are committed to supporting the goals of Arch divisions through exceptional service delivery. We pride ourselves on maintaining flexibility and responsiveness to adapt to business unit and industry demands while focusing on sound project management. We are dedicated to growing and developing our employees as we build strong teams with strategic leadership.

Arch Insurance International is a fast-growing insurance company which provides underwriting solutions across a diverse and growing portfolio of over 20 business classes, spanning multiple platforms in the London company market, the Lloyd’s market, the UK regional markets, and markets in Australia, Bermuda, and the EU.

Over the past 3 years we have increased our gross written premium from $783m to $2bn and the growth trajectory is planned to continue. Recently we were named the Top Large Insurance Employer in the Insurance Business UK Survey.

With this growth and our long-term ambitions, we are investing significantly within data, and recently setup the Chief Data Office.

Responsibilities

Keep our Party, Risk, and Reference master data accurate, complete, and trusted so downstream processes and analytics work first time.; Resolve MDM (Master Data Management) queries fast , prevent repeat issues, and drive continuous data quality improvement in Stibo STEP.

Requirements

Hands‑on MDM (Master Data Management) or data operations experience (2–5 years), ideally in customer/party and reference data domains.; Data profiling and analysis skills, comfortable with Excel/SQL basics, able to read a data model and pinpoint root causes.; Experience with ticketing (e.g., ServiceNow/Jira) and documenting repeatable fixes.; Clear, concise communicator who can explain data issues to both business and technical audiences.

Nice to have

Hands‑on MDM (Master Data Management) or data operations experience (2–5 years), ideally in customer/party and reference data domains.; Data profiling and analysis skills, comfortable with Excel/SQL basics, able to read a data model and pinpoint root causes.; Experience with ticketing (e.g., ServiceNow/Jira) and documenting repeatable fixes.; Clear, concise communicator who can explain data issues to both business and technical audiences.