Data Engineer (Dry Bulk)

TL;DR

Data Engineer (Dry Bulk): Building internal tools, analytical capabilities, and data pipelines to maintain commodity tracking data integrity with an accent on automating data quality interventions. Focus on bridging the gap between market analytics and engineering by designing scalable technical solutions for complex datasets.

Location: Hybrid, must be based in or able to work from Budapest

Company

hirify.global provides comprehensive intelligence and tracking of commodity flows across energy and maritime sectors through user-friendly data platforms.

What you will do

• Develop scripts, CLI utilities, and web-based UIs using Streamlit to improve analyst workflows.
• Query and analyze large datasets to identify data quality issues and inform strategic improvements.
• Collaborate with software engineers to build backend tools and robust data pipelines.
• Translate analyst pain points into technical solutions that reduce manual effort.
• Create automated monitoring systems to proactively flag data anomalies.
• Document tools and data processes to facilitate team knowledge sharing.

Requirements

• Proficiency in Python or ability to become proficient quickly.
• Experience extracting, transforming, and analyzing data from databases and APIs.
• Comfortable working with large, unstructured datasets.
• Familiarity with Git-based workflows and code reviews.
• Background in multidisciplinary teams with both technical and non-technical stakeholders.
• Mindset focused on delivering practical, workable solutions.

Culture & Benefits

• Focus on team collaboration and building creative solutions together.
• Commitment to a fair, inclusive, and diverse work environment.
• Opportunity to work on cutting-edge innovations in the commodities market.
• Supportive team culture that values initiative and ownership.