Data Infrastructure Engineer – ETL, NLP & Analytics

Trustmark; Ridgeland (MS); On-site; USD 80,000 - 120,000; Full time

Job summary

Trustmark Bank in Ridgeland, MS seeks a data infrastructure professional to design, evaluate, assemble, and test data systems meeting business requirements.

Responsibilities include building scalable data ingestion and processing pipelines, developing models for classification, and implementing NLP modules while maintaining data quality and governance. Strong SQL/Python skills and collaboration are essential.

Qualifications

• Bachelor's in Data or CS or equivalent certification.
• 4 years of experience with modern ETL platforms.
• Strong knowledge of relational databases, data warehousing & modeling.
• Proficiency in SQL, Python, or similar languages.
• Ability to work independently and in a team.
• Clear oral and written communication skills.
• Advanced computer skills and data warehouse expertise.
• Master’s degree in data or CS preferred.

Responsibilities

• Design, evaluate, assemble and test data infrastructures to meet business requirements.
• Build and maintain systems that collect and process data according to needs.
• Develop models for classification and information extraction from data.
• Handle data housekeeping, cleansing, normalization and schema changes.
• Develop NLP software modules.
• Troubleshoot using advanced techniques and propose solutions.
• Perform additional duties as assigned.

Skills

ETL platforms experience

SQL

Python

Analytical thinking

Problem-solving

Oral and written communication

Teamwork

Independent work

Education

Bachelor's degree in Data or Computer Science

Master’s degree relevant to data or computer sciences

Tools

IBM Datastage

Informatica

Snowpipe

Azure

AWS

Job description

Trustmark Bank in Ridgeland, MS seeks a data infrastructure professional to design, evaluate, assemble, and test data systems meeting business requirements.

Responsibilities include building scalable data ingestion and processing pipelines, developing models for classification, and implementing NLP modules while maintaining data quality and governance. Strong SQL/Python skills and collaboration are essential.