Data Engineer II
American Express (company site, opens in a new tab)4+ yrsGurugramOn-siteDirect career pageEst. 18–30 LPA
Posted 21h ago
Reach people at American Express
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at American Express you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own and enhance data pipelines and database designs to ensure performance, scalability, and security in both batch and real-time processing.
- Maintain and update data models to support business requirements and facilitate seamless integration with existing architectures.
- Provide production environment support, participate in design reviews and testing, and implement partitioning and indexing solutions for big data management.
Minimum Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or comparable experience; advanced degree preferred.
- 4+ years of experience in data engineering and development, including performance tuning of large data processing systems.
- Proficiency with SQL, Python (or Java), and experience in design and development across database management systems such as HBase, Hive, GCP tools, NoSQL databases, BigTable, BigQuery, or Cloud Spanner.
- Knowledge of distributed systems, algorithms, and database management system products including storage formats, access algorithms, replication, high availability, and encryption.
Ideal Candidate Profile
- Experienced in both batch and real-time large-scale data processing and performance tuning in Big Data environments.
- Comfortable working with GCP technologies like BigQuery, DataProc, and other cloud services relevant to data engineering.
- Collaborates effectively with cross-functional product and business teams to align technical solutions with business objectives, with a focus on operational support and delivery in Agile environments.