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Data Engineer

Treohm Analytics · Delhi, OH

📅 20/08/2026
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Company Description Treohm Analytics focuses on enabling secure, efficient access to organizational data assets to support analysis, reporting, and decision-making. The company prioritizes strong privacy guidelines and robust security controls to ensure data is handled responsibly. Team members work with modern data technologies to design and maintain systems that make trusted data readily available to stakeholders. Treohm Analytics values collaboration between engineering, analytics, and business teams to unlock the full potential of data while maintaining compliance and governance. The environment is suited for individuals who enjoy building reliable data infrastructure with a strong emphasis on security and privacy. Role Description The Data Engineer is a full-time, on-site role based in Delhi, OH. This role is responsible for designing, building, and maintaining data pipelines and storage solutions that provide efficient and secure access to data assets. Day-to-day tasks include integrating data from multiple sources, optimizing data workflows, and ensuring data quality, reliability, and performance. The Data Engineer collaborates with analysts, data scientists, and business stakeholders to understand their data needs and implement solutions that comply with privacy and security guidelines. The role also involves monitoring existing data infrastructure, troubleshooting issues, and contributing to continuous improvement of data processes and standards. Qualifications Strong skills in data engineering, including building ETL/ELT pipelines and working with relational and non-relational databases. Proficiency in programming languages commonly used for data work (such as Python, SQL, or Java) and experience with data processing frameworks. Knowledge of data security, privacy principles, and governance practices, with the ability to implement controls in data solutions. Experience with cloud or on-premise data platforms, data warehousing concepts, and performance optimization techniques. Ability to collaborate with cross-functional teams, translate business requirements into technical solutions, and communicate clearly in both technical and non-technical terms. Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience. Experience in analytics-focused or data-driven organizations is beneficial; familiarity with BI tools or data science workflows is a plus. Comfort working on-site in a collaborative environment and taking ownership of data infrastructure reliability and scalability.
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