Data Operations Specialist - Investment Data

Maintain and further develop the investment data warehouse in an SQL Server environment. Monitor daily data pipelines in Azure Data Factory and other solutions. Ensure high data quality using the automated framework, including using established data quality checks and dashboards, investigating discrepancies and escalating or solving them systematically, and performing data reconciliation. Resolve operational issues and questions (e.g. optimize queries, missing data, check consistency). Interact with users to understand the requirements and enhance their data user experience. Maintain technical documentation.

In this role as Data Operations Specialist – Investment Data, you’ll work side by side with three experienced and supportive team members who are passionate about robust, well designed data platforms. You’ll help run and improve the investment data warehouse, monitor and optimize daily data pipelines in Azure, and make sure users have clean, consistent data at their fingertips.

Zurich is a leading multi-line insurer, serving over 82 million customers in more than 200 countries and territories with more than 65,000 employees. For over 150 years, Zurich has been transforming insurance – offering not just protection, but also prevention services that promote well-being and climate resilience. Guided by its purpose to ‘create a brighter future together,’ Zurich aims to be one of the most responsible and impactful businesses in the world.

• 2–3 years working in data operations, BI support or data warehouse administration (e.g. supporting existing data platforms, scheduled jobs, and reports).

• Experience in a production environment, including monitoring daily data loads and interfaces, handling incidents and service requests, and coordinating with users and other team members.

• Experience in the financial services industry or an industry with similar requirements.

• Good understanding of investment data (e.g. securities, issuers, indices) and related structures (e.g. portfolios, holdings, company hierarchies).

• Strong practical skills in SQL for validating data, query optimization/performance tuning, and resolving issues.

• Familiarity with SQL Server environments and data warehouse concepts (comfortable navigating tables and structures).

• Working knowledge of Azure Data Factory and/or Databricks: monitor pipelines and activities; restart/re-run failed jobs, read logs and identify issues.

• Working knowledge of cloud data platforms (e.g. Databricks, Microsoft Fabric) for running jobs, checking status, and troubleshooting.

• Hands-on scripting skills in Python for automation and operational tasks (e.g. log parsing, small utilities). R is a nice-to-have.

• Working knowledge of Power BI: developing and maintaining semantic models in Power BI, validating data in the model, and implementing dashboards.