Data Steward - Static and Sustainability

UBS · Commercial & Retail Banks · Wealth Management & Financial Advisors · Python · SQL · 1 day ago

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Salary

≈ $17k – $45k per year (Estimated)

Location

In office (India)

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Oct 27, 2026. UBS scores A on the Alion truth index.

Overview

Company

Impact

Profile match

UBS

Headquartered in Zurich, Switzerland, UBS is a leading global financial services firm and one of the world's largest wealth managers. The company provides a comprehensive range of solutions, including private banking, personal and corporate banking, asset management, and investment banking services. Operating in major financial centers across the globe, the institution assists high-net-worth individuals, corporations, and institutional clients in managing and growing their assets.

ubs.com · HQ: Zurich, Switzerland · Asset Management & Funds · Investment Banking & M&A Advisory · Wealth Management & Financial Advisors · Commercial & Retail Banks · 5000+ employees · Est. 1998

Tech stack of UBS

Backed by Blue Lion

Group Functions

Are you passionate about data analytics and enjoy being a brand ambassador for high-quality cross-referenced data? Do you thrive in complex setups and have a keen attention to detail? Are you a firm believer in teamwork with the ability to motivate and innovate? Do you excel in fostering collaboration with diverse teams and stakeholders to achieve impactful outcomes? If so, this role is for you.

We're looking for a Data Steward to help us:

Execute daily client static data production and maintenance in line with SLAs and controls
Investigate cross-reference data issues across domains, document root causes, and drive sustainable fixes
Build and run structured queries using Databricks, SQL, and Python to support data quality remediation
Support product vision with input to new processes, governance, controls, and implementation
Maintain audit trails, create and update SOPs, and execute data controls, checks, and reporting

• Continuously improve process robustness and efficiency, embracing AI and building skills in data analysis

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