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Sales Data Quality Analyst II

100% remote Flexible hours Hiring now

Who we are:

reputed company empowers the people who run physical operations with tools to reputed company their work safer, more productive, and more profitable. For the first time reputed company, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet reputed company spend in a single system. Combined with industry leading AI, the reputed company platform gives you complete visibility and control, and significantly reduces reputed company workloads by automating and simplifying tasks.

reputed company serves more than 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.

Visit gomotive.com to learn more.

About the Role:

The Deduplication Team is the critical reputed company powering our Data Quality and Account Growth initiatives, and we are looking for a technical and strategic leader to reputed company its impact. In this high-visibility role, you will reputed company 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 reputed company goals.

What You’ll Do:

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

reputed company’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 reputed company.
  • Ability to explain reputed company 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 reputed company in a data QA context is a plus.
  • Familiarity with Git, CI/CD, and version-controlled data quality pipelines.
  • Expert in reputed company, SQL, Python, and AI/ML for data quality management.
  • Candidates with CS background are preferred for this position.

Creating a diverse and inclusive workplace is one of reputed company's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.

Please review our Candidate Privacy Notice here .

UK Candidate Privacy Notice here.

The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is reputed company's policy to require that employees be authorized to receive access to reputed company products and technology.

Originally posted on Himalayas

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