Data Operations Specialist - Investment Data 80-100%

Zurich Insurance

Zürich

On-site

CHF 120,000 - 170,000

Full time

8 days ago

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Job summary

Zurich Campus in Zurich is seeking a Data Operations Specialist – Investment Data to manage and improve our investment data warehouse and daily data pipelines. You will work with SQL Server, Azure Data Factory, Databricks, and Python to ensure clean, reliable data for end users.

You will deepen your SQL and cloud data tooling experience, collaborating with business users and IT colleagues to continuously optimize data flows and the user experience.

Qualifications

  • Proficient SQL for data validation and performance tuning.
  • Experience with production data loads, incidents, and monitoring.
  • Familiarity with cloud data platforms (Databricks, Fabric).
  • Hands-on scripting in Python for automation.

Responsibilities

  • Maintain and enhance the investment data warehouse (SQL Server).
  • Monitor and optimize daily data pipelines in Azure Data Factory and other tools.
  • Ensure data quality through automated checks and dashboards; investigate discrepancies.
  • Resolve data issues, optimize queries, and ensure data consistency for users.
  • Maintain documentation and engage with users to improve data UX.

Skills

SQL
Azure Data Factory
Databricks
Python
Power BI
SQL Server
Data quality

Tools

Databricks
Azure

Job description

Data Operations Specialist - Investment Data 80-100%

136822

Do you want your data skills to have a real impact on investment decisions?

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 our investment data warehouse, monitor and optimize daily data pipelines in Azure, and make sure our users have clean, consistent data at their fingertips.

You’ll get the chance to dig deep into investment data, sharpen your SQL and automation skills, and grow your experience with modern cloud data tools. If you like taking ownership, collaborating closely with business users and continuously improving how things are done, we’d be happy to hear from you

What you will do

  • 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.
    • Using established data quality checks and dashboards
    • Investigating discrepancies and escalating/solving them systematically.
    • 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

What you bring

  • 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
    • Coordinating with users and other team members.

Domain knowledge:

  • 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)

T echnical Skills:

  • 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.
  • Handson 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

You belong here.

Imagine working in one of the world’s most sustainable workplaces. At Quai Zurich Campus , you’ll enjoy an environment designed to help you thrive, with benefits that support your well‑being and impact, and opportunities to perform at your best, surrounded by top talent and supportive colleagues. You’ll have access to healthy food options, fitness facilities, and bright, collaborative spaces that spark creativity. Located in the heart of Zurich on the shores of Lake Zurich, the campus offers excellent public transportation links, making your commute simple. Grow with us through access to learning resources, on-the‑job development, and continuous empowerment and support. Be part of a team that is creating a brighter future together.

About Us

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 our purpose to ‘create a brighter future together,’ we aim to be one of the most responsible and impactful businesses in the world.

Zurich does not accept any applications from recruitment agencies for this position. We refuse any responsibility for unsolicited applications, as well as any associated fees.

At Zurich, we like to think outside the box and challenge the status quo. We take an optimistic approach by focusing on the positives and constantly asking What can go right?

We are an equal opportunity employer who knows that each employee is unique - that’s what makes our team so great! Join us as we constantly explore new ways to protect our customers and the planet.

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