Data Engineer – Document Intelligence

Company Description The Land Administration Company Inc. is a Canadian owned and operated organization delivering modern, world-class land administration solutions to jurisdictions worldwide. The team combines deep domain expertise with a strong track record of successful land administration implementations, supported by best-in-class technology partners. Guided by a vision to enable countries and citizens to own, manage, and develop land resources, the company focuses on advancing long-term social, economic, and environmental goals. LAC has developed LAVA, a leading land administration platform that provides integrated registry, cadastre, first registration, and digital survey plan submission capabilities. These solutions enhance security, service quality, productivity, and data integrity through flexible, future-proof technology and advanced integration with digital parcel fabrics. Role Description The Data Engineer – Document Intelligence will work full time on-site in Dublin, designing and maintaining data pipelines and infrastructure that support document-centric land administration solutions. This role is responsible for building and optimizing Extract Transform Load (ETL) processes, data models, and data warehouses to ingest, transform, and store structured and unstructured data from multiple sources. The Data Engineer will collaborate closely with software engineers, product teams, and domain experts to support the LAVA platform’s registry, cadastre, and digital survey workflows, ensuring data is accurate, secure, and accessible for downstream applications and analytics. Day-to-day tasks include implementing scalable data engineering solutions, optimizing performance, troubleshooting data quality issues, and contributing to the automation of document intelligence workflows. The role also involves documenting data architectures, following best practices for data governance, and continuously improving tools and processes to support global land administration projects. Qualifications - Strong data engineering skills, including experience with Data Engineering, Extract Transform Load (ETL) pipelines, and building robust data integration workflows. - Proficiency in Data Modeling and Data Warehousing, with the ability to design scalable, maintainable schemas and storage solutions for both structured and semi-structured data. - Experience with Data Analytics, including querying, profiling, and interpreting data to support business decisions and improve document intelligence capabilities. - Hands-on experience with modern data technologies (e.g., SQL and NoSQL databases, data pipeline frameworks, cloud data platforms) and scripting/programming languages commonly used in data engineering (such as Python or similar). - Knowledge of data quality, data governance, and security best practices, particularly in environments handling sensitive land and property information. - Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience. - Ability to collaborate in cross-functional teams, communicate complex data concepts in clear language, and work effectively in an on-site environment. - Experience with geospatial data, land administration