Senior Software Development Engineer II / III - Python / Pandas

Role Info :

This role sits within the merchandising space, specifically around planning and negotiations between the business and suppliers. Right now, that process is highly manual it involves back-and-forth over emails, spreadsheets, and calls, with no real system to track or manage it properly. The project is all about reimagining and building that ecosystem from the ground up.

Sr Python developer who specializes in building, automating, and maintaining large-scale data processing pipelines, integrating them with distributed data systems, and enabling high-performance search and analytics through Elasticsearch.

It requires software development skills + data pipeline automation experience, rather than a BI / reporting or pure data engineering profile.

Role overview :

• Proficient in Python, with hands-on experience using Pandas for large dataset processing.
• Solid knowledge of ETL frameworks and pipeline automation strategies.
• Experience with Elasticsearch : indexing, querying, and optimizing for performance.
• Strong command of Hive SQL and working with distributed data systems.
• Experience building APIs using Flask or similar Python frameworks.
• Understanding of data modeling, schema design, and workflow orchestration.
• Strong debugging, analytical, and communication would you do here :
• Design, develop, and automate scalable ETL workflows using Python and Pandas.
• Implement and manage data ingestion and transformation processes using Hive SQL for data warehousing.
• Configure, monitor, and optimize Elasticsearch clusters for indexing, searching, and analytics performance.
• Build and maintain RESTful APIs using Flask to facilitate secure data exchange.
• Collaborate with Data Scientists, Analysts, and Engineering teams to support data-driven applications and reporting tools.
• Ensure high standards of data quality, reliability, and integrity throughout the pipeline.
• Monitor performance, debug issues, and tune queries for maximum efficiency.
• Document data flows, pipeline architecture, and automation logic clearly.

(ref : hirist.tech)