Sales Data Quality Analyst II

About the Role:

The Deduplication Team is the critical engine powering our Data Quality and Account Growth initiatives, and we are looking for a technical and strategic leader to elevate its impact. In this high-visibility role, you will leverage deep technical expertise and sharp business acumen to transform our approach to data management. You will take ownership of many aspects of the deduplication strategy and roadmap, spearheading the creation of advanced automation and predictive models to master our vast datasets. This is more than a technical challenge; it's a unique opportunity to drive significant business results by partnering directly with stakeholders from Sales, Marketing, Operations, and Engineering. Your work will ensure our data ecosystem is not only scalable but is a primary driver of our corporate revenue goals.

What You’ll Do: 

• Architect and implement automated, AI-driven deduplication pipelines across all business segments.
• Develop predictive models for duplicate detection and prevention.
• Lead cross-functional projects with Sales, Marketing, Engineering, and Operations to align deduplication with business strategy.
• Oversee documentation, enablement, and training for deduplication processes.
• Analyze business impact and continuously optimize deduplication logic and workflows.
• Serve as the escalation point for complex deduplication and data quality issues.
• Mentor and develop team members; foster a culture of innovation and continuous improvement.

What We’re Looking For: 

• 3–5 years in data quality, data analytics, or data engineering roles.
• High level of business acumen.
• Strong problem-solving and analytical mindset.
• Ability to explain complex data issues to non-technical stakeholders.
• Deep understanding of business analytics and sales enablement.
• Proven experience designing and scaling automated solutions.
• Strong leadership, project management, and cross-functional collaboration skills.
• Exceptional communication and training abilities.
• Demonstrated impact on business outcomes through data quality initiatives.
• Experience with LLMs or generative AI in a data QA context is a plus.
• Familiarity with Git, CI/CD, and version-controlled data quality pipelines.
• Expert in Excel, SQL, Python, and AI/ML for data quality management.
• Candidates with CS background are preferred for this position.