Enterprise Data Engineer: Build & Scale Data Pipelines

Trustmark National Bank; Panhandle (TX); On-site; USD 110,000 - 160,000; Full time

Job summary

Trustmark National Bank is seeking an Enterprise Data Engineer to design, evaluate, assemble, and test data infrastructures that meet business requirements.

The role involves building and evolving complex data systems, ingesting and processing data, and developing NLP components to extract meaning from data. Collaboration with analytics teams and compliance with data governance are essential.

Qualifications

• Bachelor's degree in Data or Computer Science or equivalent certification.
• 4+ years of experience with modern ETL platforms (IBM Datastage, Informatica, Snowpipe, Azure, AWS).
• Strong knowledge of relational databases, data warehousing, and data modeling.
• Proficient in SQL, Python, and data analysis techniques.
• Excellent oral and written communication skills.

Responsibilities

• Designs, assembles, and tests data infrastructures to meet business requirements.
• Builds, evolves, and scales data ingestion and processing pipelines.
• Develops models for classification and information extraction from data.
• Performs data cleansing, normalization, and schema changes; analyzes data for trends and anomalies.
• Develops NLP software modules for data processing tasks.
• Troubleshoots issues and identifies solutions; performs other duties as assigned.

Skills

SQL

Python

Analytical thinking

Problem-solving

Oral and written communication

Education

Bachelor's degree in Data or Computer Science

Master's degree related to data or computer sciences (preferred)

Tools

IBM Datastage

Informatica

Snowpipe

Azure

AWS

Job description

Trustmark National Bank is seeking an Enterprise Data Engineer to design, evaluate, assemble, and test data infrastructures that meet business requirements.

The role involves building and evolving complex data systems, ingesting and processing data, and developing NLP components to extract meaning from data. Collaboration with analytics teams and compliance with data governance are essential.