Data Engineer

Job Summary We are seeking a talented and driven Data Engineer to support the modernization of the client's data infrastructure and drive enterprise-wide data excellence. In this role, you will be responsible for rebuilding our data foundation—covering ingestion, validation, and standardized transformations—with the strategic goal of transitioning full ownership of data pipelines to IT and eliminating manual processes. As a key member of our technology team, you will leverage your expertise in Microsoft Fabric (including Lakehouse, Data Warehouse, Dataflow Gen2, and pipelines) to design and implement scalable, reliable data solutions. You will play a critical role in developing robust ETL/ELT pipelines and architecting modern data platforms that enable efficient data access, governance, and analytics across the organization. The ideal candidate brings strong hands-on experience with SQL and/or Spark-based transformations, along with a deep understanding of data engineering best practices. What sets INVID apart is our collaborative and flexible work environment. We encourage our team to raise the bar in everything they do while maintaining a healthy work-life balance. With our hybrid work model, team members thrive both in the office and remotely. We foster a culture of mutual respect, autonomy, and accountability, where your voice matters and your growth is supported. From structured career paths and paid professional development to access to industry events, we’re committed to your success. Duties and Responsibilities Design, build, and orchestrate scalable data pipelines using Microsoft Fabric to support efficient data ingestion, transformation, and delivery. Implement and manage a robust medallion (Bronze/Silver/Gold) architecture to enhance data quality, consistency, and usability. Develop and maintain transformation logic, including data cleansing, standardization, deduplication, and mapping, while modernizing legacy processes by migrating Python-based workflows into Fabric-native solutions. Ensure strong data governance by implementing validation, quality checks, and end-to-end traceability across pipelines. Continuously optimize data processing and refresh strategies to support near real-time reporting and reduce data latency. Teamwork and Communication Work under Agile methodologies and frameworks such as Scrum or Kanban. Provide daily status and feedback on the work performed. Assist in the analysis, design, development, and deployment of necessary data. Provide accurate explanations of any written code. Communicate with internal and external personnel in English or Spanish to discuss requirements and specifications, provide status updates, and explain the work performed. Required Qualifications 7+ years of experience in data engineering, data integration, or related roles Strong hands-on experience with Microsoft Fabric (Lakehouse, Data Warehouse, Dataflow Gen2, pipelines) Proven expertise in designing and implementing ETL/ELT pipelines and scalable data architectures Strong proficiency in SQL and/or Spark-based transformations Experience with data quality, validation, and lineage concepts Demonstrated experience working with large, complex datasets in cloud environments Proven ability to modernize legacy data processes and automate manual workflows Preferred Qualifications Experience with Python (pandas, scripting) to interpret and refactor existing transformation logic Familiarity with the Azure data ecosystem and integration patterns Experience supporting near real-time data processing environments Strong communication and collaboration skills Other requirements: US Resident | US Citizenship Fully Bilingual (Spanish and English) Work Modality: Hybrid Location: San Juan, Puerto Rico Benefits and Perks We believe in supporting our employees’ well-being, growth, and work-life balance. As part of our team, you will have access to a comprehensive benefits package that includes: Paid time off, including vacation and sick leave Company-sponsored health insurance coverage Retirement plan to help you plan for the future Hybrid work model offering flexibility between office and remote work Flexible working hours to support work-life balance Continuing education reimbursement to encourage professional development Company-paid life insurance EEO