Data EngineerWe 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 ResponsibilitiesDesign, 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 CommunicationWork 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 Qualifications7+ years of experience in data engineering, data integration, or related rolesStrong hands-on experience with Microsoft Fabric (Lakehouse, Data Warehouse, Dataflow Gen2, pipelines)Proven expertise in designing and implementing ETL/ELT pipelines and scalable data architecturesStrong proficiency in SQL and/or Spark-based transformationsExperience with data quality, validation, and lineage conceptsDemonstrated experience working with large, complex datasets in cloud environmentsProven ability to modernize legacy data processes and automate manual workflowsPreferred QualificationsExperience with Python (pandas, scripting) to interpret and refactor existing transformation logicFamiliarity with the Azure data ecosystem and integration patternsExperience supporting near real-time data processing environmentsStrong communication and collaboration skillsOther requirements:US Resident | US CitizenshipFully Bilingual (Spanish and English)Work Modality: HybridLocation: San Juan, Puerto RicoBenefits and PerksWe 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 leaveCompany-sponsored health insurance coverageRetirement plan to help you plan for the futureHybrid work model offering flexibility between office and remote workFlexible working hours to support work-life balanceContinuing education reimbursement to encourage professional developmentCompany-paid life insurance