Senior Data Engineer - Remote/Hybrid, OLAP & ETL Expert

American Express; Phoenix (AZ); On-site; USD 27,552 - 41,328; Full time

Benefits offered by this job

Remote work 3 days/week

6% retirement plan match

Comprehensive health benefits

Job summary

American Express is seeking a Senior Data Engineer in Phoenix, AZ to design and optimize data architectures that support business insights. You will work with Hadoop/Hive ecosystems, relational data warehouses, and modern data tools to enable reliable data delivery.

Responsibilities include defining data requirements, developing data models, and maintaining data pipelines from ingestion to analytics. 2+ years in data collection and warehouse environments is expected.

Qualifications

• Degree in Computer Science, Information Systems, or related STEM field.
• 2 years of practical data collection experience.
• 2 years of experience building and tuning with a relational data warehouse (RDMS).
• 2 years of experience in data warehouse development and OLTP/OLAP support.
• 2 years applying advanced data modeling and data management methods.
• 2 years of experience with large-scale data technologies (MPP, Hadoop ecosystem).

Responsibilities

• Define data requirements and data sources to support data designs.
• Develop and maintain database architectures for the business portfolio.
• Plan data collection strategies and translate needs into data collection plans.
• Oversee data warehouse development and data indexing for ongoing operations.
• Support data collection plans, testing, and index structures.
• Design features for continuous data operations and performance.

Skills

SQL tuning

Data modeling

Python programming

Data governance

Communication

Education

Graduate

Tools

Apache Hadoop

Hive

Glimmer

IBM DB2

Kafka

MemSQL

MySQL

Netezza

PostgreSQL

Python

PL/SQL

Sqoop

Job description

American Express is seeking a Senior Data Engineer in Phoenix, AZ to design and optimize data architectures that support business insights. You will work with Hadoop/Hive ecosystems, relational data warehouses, and modern data tools to enable reliable data delivery.

Responsibilities include defining data requirements, developing data models, and maintaining data pipelines from ingestion to analytics. 2+ years in data collection and warehouse environments is expected.