Lead Data Engineer (Microsoft Fabric)

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients.

What is this position about? Conduct comprehensive gap analysis and data mapping across 80+ ERP systems to identify integration challenges, data inconsistencies, and transformation requirements. Design and develop standardized ETL pipelines and data transformation processes for migrating enterprise data into Microsoft Fabric. Build robust data quality frameworks and validation rules to ensure data readiness for AI and analytics workloads. Lead hands-on implementation of ETL standards and best practices, establishing repeatable patterns and automation scripts for multi-source integrations. Develop and optimize data models that support seamless transformation from fragmented ERP sources into a unified, AI-ready data architecture. Lead the pilot implementation phase, testing and refining standards against real ERP data before full-scale rollout. Mentor and guide team members on ETL development, data transformation techniques, and Fabric-specific engineering practices. Collaborate with stakeholders to document data lineage, transformation logic, and integration patterns for knowledge transfer and governance. Troubleshoot data inconsistencies and implement corrective measures to maintain data integrity throughout the pipeline.

Advanced proficiency in SQL for complex data transformations, query optimization, and performance tuning. Strong Python expertise for automation scripting, data pipeline development, and ETL orchestration. Demonstrated hands-on experience in designing and implementing ETL solutions across complex, multi-source environments. Proven experience with enterprise ERP systems and large-scale data integration scenarios. Solid understanding of Azure ecosystem and hands-on experience with Microsoft Fabric for data engineering. Strong knowledge of data modeling principles and ability to design schemas that support AI and analytics use cases. Experience with data quality assessment, validation frameworks, and data profiling techniques. Excellent problem-solving skills with a focus on scalability, maintainability, and performance optimization. Strong communication skills and ability to collaborate with technical and business stakeholders. What about languages? English: Advanced (required for effective communication with global teams) How much experience must I have? 5+ years of experience in Data Engineering with demonstrated expertise in data modeling and ETL development.

Our Perks and Benefits: 📚 Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. Access to AI learning paths to stay up to date with the latest technologies. Study plans, courses, and additional certifications tailored to your role. Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. English lessons to support your professional communication. 👨🏽‍💻 Travel opportunities to attend industry conferences and meet clients. 👩‍🏫 Mentoring and Development: Career development plans and mentorship programs to help shape your path. 🎁 Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. Company-provided equipment. ⚖️ Flexible working options to help you strike the right balance. Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters. So what are the next steps? Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we'll explore working together!