Website:
tri-nexa.com
Job details:
Company Description TriNexa is a technology consulting and engineering company focused on transforming ideas into intelligent solutions using AI, data engineering, and next-generation technologies. The team builds scalable digital platforms and enables data-driven innovation to help businesses thrive in a rapidly evolving digital world. TriNexa’s core capabilities span AI solutions, data engineering, cloud engineering, web and mobile development, DevOps and automation, and data analytics and business intelligence. The company is in an early, high-growth phase and emphasizes continuous learning, innovation, and thought leadership in digital transformation.
Role Description As a Senior Data Engineer at TriNexa, you will design, build, and maintain scalable data pipelines and platforms that power AI, analytics, and digital products. This full-time remote role involves architecting robust data solutions, implementing ETL processes, and optimizing data models and warehouses for reliability, performance, and cost-efficiency. You will collaborate closely with data scientists, analysts, and software engineers to ensure data is accurate, accessible, and secure across multiple systems and environments. Typical responsibilities include evaluating new tools and frameworks, enforcing best practices for data quality and governance, troubleshooting complex data issues, and contributing to technical standards and documentation. You will also mentor team members, participate in code reviews, and help shape the overall data engineering strategy for client and internal projects.
Qualifications
- Candidates should possess strong data engineering skills, including experience with modern data platforms, distributed processing frameworks (e.g., Spark), and scripting or programming languages commonly used in data engineering.
- Candidates should possess data modeling and data warehousing skills, with the ability to design efficient schemas, implement dimensional models, and support scalable analytical workloads.
- Candidates should possess Extract Transform Load (ETL) skills, including building, orchestrating, and monitoring reliable data pipelines using ETL tools or workflow frameworks.
- Candidates should possess data analytics skills, with proficiency in querying large datasets, using SQL and analytical tools, and supporting business intelligence and reporting needs.
- Relevant skills and qualifications include experience with cloud data services (e.g., AWS, Azure, or GCP), familiarity with DevOps practices for data systems, and knowledge of data security and governance.
- A bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
- Demonstrated ability to work effectively in remote, cross-functional teams, strong communication skills, and a track record of delivering high-quality data solutions in production environments.
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