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American Express Lead Analyst Jobs 2026

Risk / Analytics / Sales Enablement | Gurugram

Posted: May 2026
Gurugram, Haryana (Hybrid)
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Experience
1–2 Years
Qualification
Bachelor’s Degree
Salary
Competitive
Job ID
26007567

Job Overview

American Express is hiring Lead Analysts for its Global Commercial Services (GCS) team in Gurugram, India.

The role focuses on data analytics, sales insights, reporting automation, and stakeholder support to help drive business growth and operational efficiency across commercial payment solutions. The company is looking for candidates with strong analytical capabilities, SQL and HIVE expertise, and experience working with data-driven business insights.

💡 Why this role?

This role is ideal for professionals interested in analytics, reporting, automation, and business intelligence within a global financial services environment, allowing you to directly influence strategic sales decisions.

Roles & Responsibilities

  • Monitor sales efforts and track business opportunities meticulously using internal analytical systems.
  • Drive data analytics and build reporting frameworks utilizing SQL, HIVE, and advanced data tools.
  • Prepare comprehensive reports, performance metrics, and business insights to guide leadership teams in strategic decision-making.
  • Identify robust automation opportunities, enhancing reporting workflows to dramatically improve operational efficiency.
  • Perform rigorous quality checks on sales documentation, support product managers with insights, and act as a subject matter expert for US SME processes.

Eligibility Criteria

Education

Bachelor’s Degree in a relevant analytical, business, or technical field.

Experience

1–2 years of relevant work experience in analytics or reporting roles, particularly working with large datasets.

Technical & Core Competence

Strong expertise in SQL and HIVE. Deep understanding of data analytics, data interpretation, and business metrics analysis. Advanced MS Excel skills. Experience in reporting, dashboarding, automation techniques, and data quality validation.

How to Apply

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