Blend360 Principal Data Engineer \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . Principal Data Engineer Full-time Company Description Blendis 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. For more information, visit www.blend360.com This position is for Colombia, Argentina and Uruguay. Job Description We are looking for a Principal Data Engineer to own and build the production-grade data layer that powers a Claims AI / Intelligent Suite running on Azure Databricks. This is a hands-on role embedded in the delivery team, responsible for ingestion, transformation, storage, quality, and serving of claims-related data used by AI models and agent workflows. You will work closely with AI Engineers, the Lead Databricks Architect, and the clients Cloud and Platform teams to ensure data pipelines and data foundations are reliable, scalable, and ready for AI-driven workloads. This is not a BI or reporting role: the primary consumers of your work are AI systems, agents, and vector search pipelines. Design, build, and maintain production-grade data pipelines in Azure Databricks using Delta Live Tables and Structured Streaming. Implement and operate medallion architecture (bronze, silver, gold) with clear data contracts, quality controls, and freshness SLAs. Build and maintain scalable data models and feature tables for claims, policies, litigation, and adjuster data. Engineer data preparation pipelines for AI workloads, including structured data serving and unstructured document processing for vector search and RAG use cases. Enforce data quality, observability, and reliability through automated checks, lineage, schema enforcement, and freshness monitoring. Own pipeline orchestration, CI/CD, monitoring, and failure recovery for production data systems. Collaborate closely with AI Engineers and the Lead Databricks Architect to align data architecture with agentic AI and platform decisions. Work with client data owners and platform teams to manage data access, upstream changes, and source system dependencies. Qualifications 7+ years of experience in Data Engineering with strong hands-on experience building production pipelines on Databricks (PySpark, Delta Lake, DLT) Databricks is a must. Deep knowledge of Delta Lake optimization, streaming and batch patterns, schema evolution, and performance tuning. Solid experience with Unity Catalog, data governance, and secure data access patterns. Strong SQL and PySpark skills, with a production engineering mindset. Experience building CI/CD for data pipelines and operating data systems in production. Strong Azure fundamentals (ADLS Gen2, identities, Key Vault, security and networking concepts). Data quality and reliability mindset with experience implementing observability and quality frameworks. Ability to work independently and take ownership after high-level direction is provided (run with the ball). Experience with Insurance (P&C / Commercial Liability) and AI/ML data platform experience is a strong plus. Databricks Data Engineer Professional or Azure Data Engineer Associate certification is a plus. What about languages? You will need excellent written and verbal English for clear and effective communication with the team. Additional Information 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 well explore working together! I'm interested I'm interestedPrivacy Notice ImprintCookies Settings I'm interested Refer a friend share this job Share on LinkedIn Share on Facebook Share on Twitter Share via email Share on Xing Share on WeChat Share to WeChat × Copy the link and open WeChat to share. Copy to clipboard Open WeChat Share to WeChat × Use Scan QR Code in WeChat and click ··· to share. Principal Data Engineer Bogotá, Bogota, Colombia Full-time I'm interested I'm interested

The role requires over seven years of experience in Data Engineering with significant hands-on experience building production pipelines on Databricks, including PySpark, Delta Lake, and DLT. Deep knowledge of Delta Lake optimization, streaming and batch patterns, schema evolution, and performance tuning is essential. Solid experience with Unity Catalog, data governance, and secure data access patterns is also necessary. Strong SQL and PySpark skills, coupled with a production engineering mindset and experience building CI/CD for data pipelines, are required. Familiarity with Azure fundamentals, including ADLS Gen2, identities, Key Vault, security, and networking concepts, is important. A data quality and reliability mindset with experience in observability and quality frameworks is expected. The ability to work independently and take ownership is also a key qualification. Experience with Insurance and AI/ML data platforms is a strong plus.