American Express Recruitment Drive; Hiring Data Engineer Analyst – Apply Now

They are seeking a Data Engineer to help drive the design and development of a robust data infrastructure, through building databases and pipelines that will support their planning processes, Machine Learning use-cases and leadership reporting. As a Data Engineer, you will be part of a team responsible for the development and execution of world-class advanced analytics projects, leveraging automation and machine learning to enhance and streamline business processes. You will build scalable solutions that benefit their internal customers – from technical design, prototyping, testing, deploying and monitoring production data. The ideal candidate will have the skills to collaborate in a cross-functional environment – planning, operations, finance, forecasting, data science – to test new ideas and challenge conventions.  

Name of the Organization: American Express

Requisition ID: 25000190

Positions: Analyst-Data Engineer

Location: Gurugram (Hybrid)

Salary: As per company Norms

Required Skills & Qualifications:

• Previous experience in a Data Engineer or Data Architect based role
• Knowledge of common data structures for storage and online analytical processing. 
• Proficiency in Google Cloud Platform services or equivalent relevant Cloud infrastructure services.
• Proficiency in a querying language: any in the SQL suite or similar 
• A deep grasp of computer science fundamentals and applied principles
• Experience in version control (GIT) for coordinating work and code releases.
• Ability to communicate with both technical and non-technical audiences
• Ability to justify design choices and assumptions

Preferred Qualifications:

• Expertise in tools like Tableau, Power BI or similar platforms to create clear impactful visual reports.
• Familiarity with Python and object-oriented programming.
• Experience developing machine learning workflows and supporting Data Science projects
• Previous exposure to delivering using Agile development practices.

Responsibilities:

• Support GCCM colleagues migrating production-grade data and pipelines to the Google Cloud Platform
• Help define and apply data governance requirements for accurate and consistent storing of data records
• Build and adapt querying scripts and data pipelines to prepare the operational data layers used for Analytics
• Implement quality monitoring and control throughout the systems you develop
• Deploy autonomous reliable solutions and logging systems so that services remain online 24/7 without human intervention.
• Build well-engineered and documented code in collaboration with other developers.
• Co-design and build scalable ETL pipelines in a complex data environment. 
• Ability to manage time, prioritize tasks, negotiate requirements in an Agile Framework.
• Help define best practices for a data ecosystem that will support Machine learning and future AI research.
• Collaborate with data scientists and business analysts by facilitating their data format and condition requirements

 

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