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At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way. When you join #TeamAmex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day.
Functional Description:
Enterprise Comms & MarTech Experiences (ECMX) is a global organization that sits within U.S. Consumer Services (USCS) and is American Express’ marketing services center of excellence with the charter of driving high quality, customer-first marketing that accelerates business growth through optimized go-to-market solutions and the development of best-in-class MarTech products & processes.
Purpose of the role:
The candidate would be part of the Product Team for MarTech – UMDL (Unified Marketing Data Layer) and support data quality enablement and monitoring across UMDL products. The role will focus on helping the team define, track, validate, and report data quality checks for marketing data products used across global markets. The candidate will work closely with product, business, and technology partners to understand data definitions, analyze exceptions, document issues, and support timely remediation.
We are looking for an early-career candidate from a reputed college with strong analytical skills and hands-on knowledge of SQL, Excel, and BigQuery. Exposure to data profiling, reporting, and basic automation will be an added advantage.
- Support data quality enablement and monitoring for UMDL products across agreed data domains and use cases
- Run SQL and BigQuery-based checks to validate data completeness, accuracy, consistency, and timeliness
- Prepare Excel-based trackers, dashboards, and summaries to report data quality trends and open issues
- Analyze data quality exceptions, document observations, and support root-cause discussions with product and technology teams
- Maintain data quality rules, issue logs, process documentation, and recurring monitoring reports
- Identify opportunities to simplify recurring monitoring activities through standard templates, reusable queries, and basic automation
Business Outcomes:
- Improve visibility into data quality health across UMDL products through recurring monitoring and clear reporting
- Support timely identification, tracking, and closure of data quality issues impacting marketing use cases
- Enable product teams with accurate data quality insights, issue documentation, and trend analysis for decision-making
Leadership Outcomes:
- Put enterprise thinking first, connect the role’s agenda to enterprise priorities and balance the needs of customers, partners, colleagues and shareholders.
- Lead with an external perspective, challenge status quo and bring continuous innovation to our existing offerings
- Demonstrate learning agility, make decisions quickly and with the highest level of integrity
- Lead with an enterprise mindset and deliver the world’s best customer experiences every day
- 0–1 year of experience, including internships, academic projects, or entry-level work in data analysis, reporting, or data quality monitoring
- Strong foundation in SQL and Excel, with ability to analyze datasets, identify patterns, and summarize findings
- Exposure to BigQuery, GCP, Python, or data visualization tools will be an added advantage
Academic Background:
- Bachelor’s or Master’s degree from a reputed college in a non-B.Tech discipline such as Statistics, Mathematics, Economics, Commerce, Business Analytics, Computer Applications, or related quantitative field
- Strong academic performance with demonstrated interest in data analytics, data management, or business reporting
Functional Skills:
- Basic understanding of data quality concepts such as completeness, accuracy, consistency, timeliness, and reconciliation
- Ability to translate business questions into data checks, summaries, and actionable insights
- Good communication, documentation, and collaboration skills with attention to detail and willingness to learn
Technical Skills:
- Strong SQL skills for querying, joining, filtering, aggregating, and validating large datasets
- Strong Excel skills, including pivot tables, lookups, formulas, data validation, and structured reporting
- Working knowledge of BigQuery or similar cloud-based data platforms is advantageous
- Ability to perform data profiling, exception analysis, reconciliation, and recurring monitoring
Apprenticeship Duration
- 6 months