Dun & Bradstreet, Inc. logo

Customer Service (Apprentice)

Job Overview

Location

Mumbai - India

Job Type

Full-time

Category

Data Science

Date Posted

May 23, 2026

Full Job Description

đź“‹ Description

  • • Serve as an apprentice in the Operations team supporting Dun & Bradstreet’s Products SBU, gaining hands-on experience in business decisioning data and analytics workflows.
  • • Assist in processing, validating, and maintaining high-quality business data used by global clients to make informed commercial decisions.
  • • Collaborate with cross-functional teams to ensure data accuracy, consistency, and timely delivery across internal systems and client-facing platforms.
  • • Learn and apply standard operating procedures for data ingestion, cleansing, and enrichment processes within a regulated, enterprise-grade environment.
  • • Support daily operational tasks including monitoring data pipelines, identifying anomalies, and escalating issues to senior team members for resolution.
  • • Participate in training sessions and onboarding programs designed to build foundational knowledge in business data, analytics, and customer-centric operations.
  • • Contribute to continuous improvement initiatives by documenting process gaps, suggesting efficiency enhancements, and adhering to quality control standards.
  • • Work within a structured apprenticeship framework that combines mentorship, performance feedback, and skill development tailored to operational excellence.
  • • Engage with global stakeholders to understand client data needs and ensure internal operations align with customer expectations and service level agreements.
  • • Maintain strict compliance with data privacy, security protocols, and company policies while handling sensitive business information.
  • • Utilize internal tools and platforms to track task progress, update case logs, and report operational metrics to team leads on a regular basis.
  • • Develop familiarity with Dun & Bradstreet’s proprietary data products and how they support risk management, credit evaluation, and market intelligence for enterprises worldwide.
  • • Adapt to evolving operational priorities and contribute to team goals in a fast-paced, results-driven environment.
  • • Receive structured guidance from experienced operations professionals to build a career path in data operations, customer support, or business analytics.

🎯 Requirements

  • • Willingness to learn and apply structured operational processes in a data-intensive environment
  • • Strong attention to detail and accuracy in handling large volumes of business information
  • • Basic proficiency in using digital tools and systems for task tracking and data entry
  • • Ability to work collaboratively in a team-oriented, global organization
  • • Good communication skills in English, both written and verbal
  • • Availability to work in Navi Mumbai, India, with adherence to scheduled shifts

🏖️ Benefits

  • • Structured apprenticeship program with mentorship and career development pathways
  • • Access to Dun & Bradstreet’s global training resources and internal learning platforms
  • • Opportunity to gain exposure to enterprise-level business data and analytics systems
  • • Competitive stipend and performance-based incentives for apprentices

Skills & Technologies

Onsite

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Dun & Bradstreet, Inc. logo
Dun & Bradstreet, Inc.
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About Dun & Bradstreet, Inc.

Dun & Bradstreet is a global provider of commercial data, analytics and insights on businesses. The company maintains a database of more than 500 million corporate entities worldwide, offering credit reports, risk management tools, sales and marketing intelligence, supply chain data, and compliance solutions. Founded in 1841, it serves enterprises, financial institutions and governments seeking to assess business creditworthiness, identify opportunities and mitigate risk. Its offerings are delivered through cloud-based platforms and APIs, integrating with customer systems to support informed decision-making across finance, procurement and regulatory functions.

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