Senior Data Engineer

Company Description TriNexa is a technology consulting and engineering company focused on turning ideas into intelligent solutions through AI, data engineering, and next-generation technologies. The company builds scalable digital platforms and enables data-driven innovation to help businesses succeed in a fast-changing digital landscape. TriNexa’s capabilities span AI solutions, data engineering, cloud engineering, web and mobile development, DevOps and automation, and data analytics and business intelligence. The team is committed to continuous learning, sharing insights, and driving digital transformation for clients across industries. Joining TriNexa means contributing to the journey of building the future through technology.
Role Description The Senior Data Engineer is a full-time remote role responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support advanced analytics and AI solutions. In this position, the Senior Data Engineer will work closely with data scientists, software engineers, and business stakeholders to define data requirements, integrate diverse data sources, and ensure data quality and reliability. Day-to-day tasks include implementing ETL processes, optimizing data workflows, modeling data for analytics and reporting, and administering data warehouses and data platforms in cloud environments. The role also involves monitoring performance, troubleshooting data issues, implementing best practices for security and governance, and contributing to architectural decisions and technical standards. The Senior Data Engineer will mentor other team members, participate in code reviews, and help drive continuous improvement across TriNexa’s data engineering practices.
Qualifications
Strong data engineering skills, including experience designing and implementing scalable data pipelines and working with modern data platforms.
Proficiency in data modeling and data warehousing, with the ability to design schemas that support analytics, reporting, and high-performance querying.
Hands-on experience with Extract Transform Load (ETL) processes and tools, including building, scheduling, and monitoring robust data workflows.
Practical knowledge of data analytics, including preparing data for dashboards, reports, and advanced analytics or machine learning use cases.
Experience with cloud data ecosystems (e.g., AWS, Azure, or GCP), SQL and one or more programming languages commonly used in data engineering (such as Python or Scala).
Understanding of data governance, security, and compliance best practices, including data quality management and documentation.
Ability to collaborate effectively in remote, cross-functional teams, communicate complex technical concepts clearly, and lead technical discussions.
Bachelor’s or master’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.

Work arrangement
Yes