Data Ingestion Engineer - Applications (Remote)

Ross Stores; Dublin (CA); On-site; USD 81,000 - 136,000; Full time

Job summary

Ross Stores is seeking an Applications Analyst to help develop and support data ingestion workflows using StreamSets, write Python scripts for data processing, and assist in integrating data from cloud and data lake environments.

The role emphasizes monitoring pipelines, adherence to development and deployment processes, and learning best practices in data integration and security while collaborating with a growing, diverse team.

Qualifications

• Bachelor's degree in computer science, information technology, or a related field is required.
• 3-5 years of experience with StreamSets or similar data ingestion tools.
• Experience with writing Python or other scripting languages for data processing.

Responsibilities

• Assist in development and maintenance of data ingestion pipelines using StreamSets or similar tools.
• Write and support Python scripts for data processing, integration, and validation tasks.
• Monitor data pipelines and production systems, identify issues, and elevate as needed for resolution.
• Support implementation of data ingestion solutions within cloud and data lake environments.
• Collaborate with team members to follow established development, testing, and deployment processes.
• Perform routine system checks, ensure adherence to operational procedures, and support documentation updates.
• Learn and apply best practices in data integration, security, and system performance optimization.

Skills

StreamSets

Python

Data formats (JSON/XML/CSV)

Cloud basics

OS knowledge (Linux/Windows)

Security basics

Troubleshooting

Team collaboration

Education

Bachelor's degree in CS/IT or related field

Tools

StreamSets

Job description

Ross Stores is seeking an Applications Analyst to help develop and support data ingestion workflows using StreamSets, write Python scripts for data processing, and assist in integrating data from cloud and data lake environments.

The role emphasizes monitoring pipelines, adherence to development and deployment processes, and learning best practices in data integration and security while collaborating with a growing, diverse team.