Data Quality Analyst

Quavo Fraud & Disputes

2d

About The Position

The Data Quality Analyst ensures that the data powering Quavo’s dispute management platform and client reporting is accurate, complete, and trustworthy. Working with the Data Engineering team, this role defines and monitors data quality rules across the Snowflake data platform, investigates anomalies at their source, and drives fixes with engineering and product teams. The analyst serves as a first line of defense between upstream system changes and the metrics relied on by financial institution clients, internal teams, and leadership. The work reduces reporting errors, protects client trust, and supports compliance and audit commitments.

This role is not eligible for visa sponsorship. Applicants must be legally authorized to work in the United States without employer visa sponsorship, now or in the future.

Requirements

• 3–5 years of experience in data quality, data analysis, data validation, or a related data role.
• Strong SQL skills, including joins, window functions, aggregations, and queries for profiling and reconciling large datasets.
• Hands-on experience with a cloud data warehouse, preferably Snowflake.
• Experience investigating data issues end to end: reproducing problems, isolating root causes, and documenting fixes.
• Working knowledge of Python or a similar scripting language for data checks and automation.
• Familiarity with data quality dimensions, data profiling techniques, and testing approaches for ETL/ELT pipelines.
• Experience with a BI or reporting tool such as Omni, Tableau, Power BI, or Looker.
• Comfort working with semi-structured data such as JSON and multiple source systems.
• Clear written communication skills, including the ability to explain data issues and their business impact to technical and non-technical audiences.
• Experience working in Jira and Confluence, or similar ticketing and documentation tools.

Nice To Haves

• Bachelor’s degree in Information Systems, Computer Science, Statistics, Mathematics, or a related field, or equivalent experience.
• SnowPro Core Certification or another data platform, analytics, or data management certification such as CDMP.
• Experience with data observability tools such as Metaplane, Monte Carlo, or Datadog, or testing frameworks such as dbt tests or Great Expectations.
• Familiarity with Pega, including its data model, case types, or integrations.
• Background in financial services, payments, card disputes, or fraud.
• Familiarity with regulated data environments such as PCI DSS and SOC 1/SOC 2, and with row-level security or multi-tenant data models.

Responsibilities

• Define, implement, and maintain data quality checks for completeness, accuracy, validity, timeliness, and uniqueness across Snowflake ingestion pipelines, dynamic tables, and reporting layers.
• Monitor data observability alerts for freshness, volume, schema changes, and distribution drift; triage incidents and route root causes to the owning team with clear evidence.
• Investigate data discrepancies reported by clients, Customer Success, and internal stakeholders, tracing issues upstream through lineage to the originating system or transformation.
• Reconcile key metrics and record counts between source systems, the data warehouse, and client-facing reports and data shares.
• Maintain business metric definitions and data documentation in partnership with metric owners, keeping the metric library and data dictionary current.
• Validate new pipelines, schema changes, and client onboarding data before release, including multi-tenant isolation and access-control checks.
• Build and maintain data quality dashboards and scorecards tracking issue volume, time to resolution, and rule coverage.
• Uphold data handling standards for sensitive and regulated data, including PII and PCI, and support SOC audit evidence requests and data governance controls.
• Document recurring issues and recommend preventive fixes to pipelines, source system integrations, and data contracts.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed