DataStage ETL Engineer: High-Volume Data Integration

Artifintech; Plano (TX); On-site; USD 85,000 - 130,000; Full time

Job summary

ARTIFICIAL INTELLIGENCE TECHNOLOGIES LLC in Plano, TX, seeks an experienced ETL developer to design and implement data integration solutions using IBM DataStage.

You will collaborate with cross-functional teams, optimize ETL processes, troubleshoot issues, maintain batch jobs, and ensure data quality across environments.

Strong skills in data quality, source/target mapping, performance tuning, and high-volume data loads will help drive successful project delivery.

Qualifications

• Experience with data integration and ETL tooling.
• Ability to troubleshoot, operate, test, plan and/or configure in relevant technologies.
• Strong collaboration with QA/BA/SMEs and project teams.

Responsibilities

• Develop and implement data integration solutions using IBM DataStage.
• Collaborate with cross-functional teams to ensure successful application delivery.
• Optimize ETL processes to enhance data quality and performance.
• Troubleshoot and resolve issues related to data integration and application functionality.
• Maintain the batch jobs and coordinate changes across environments for releases.
• Work with project teams to discuss issues and provide solutions meeting business and technical requirements.
• Identify and implement system enhancements and automation.
• Document procedures and processes clearly.
• Work in process automation using Shell Scripts and SQL.
• Knowledge of Splunk and other monitoring tools.

Skills

IBM DataStage

ETL

Data Quality

Source-Target Mapping

SQL

Shell scripting

Splunk

Monitoring tools

Documentation

Tools

Shell scripting

Splunk

Monitoring tools

Job description

ARTIFICIAL INTELLIGENCE TECHNOLOGIES LLC in Plano, TX, seeks an experienced ETL developer to design and implement data integration solutions using IBM DataStage.

You will collaborate with cross-functional teams, optimize ETL processes, troubleshoot issues, maintain batch jobs, and ensure data quality across environments.

Strong skills in data quality, source/target mapping, performance tuning, and high-volume data loads will help drive successful project delivery.