Data Engineer Lead

Company Description: 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. For more information, visit www.blend360.com Job Description: We are looking for a Data Engineer to design and build scalable data platforms that enable advanced analytics, forecasting, and customer retention use cases. This role focuses on developing robust data pipelines, integrating complex data sources, and delivering high-quality, model-ready datasets for both BI and AI-driven initiatives. You will work closely with data, analytics, and business teams to ensure data is reliable, well-structured, and accessible for decision-making, while supporting both operational reporting and advanced modeling use cases. You may work 100% remotely if you are currently living in LATAM, or you can always join us at the office! Job Description • Design, build, and maintain scalable ETL/ELT pipelines using Python and SQL on modern lakehouse architectures. • Develop data solutions using tools such as Azure Data Factory, Synapse, Fabric, Airflow, or dbt. • Build and maintain data models and pipelines that support forecasting and customer retention/churn use cases, including feature engineering and reproducibility. • Integrate data from multiple transactional systems (ERP, CRM, etc.), ensuring proper standardization, entity resolution, and consistency across datasets. • Implement data quality frameworks, validation processes, and monitoring to ensure reliability and accuracy of data pipelines. • Design dimensional and semantic data models to support BI and analytics consumption, enabling drill-down capabilities from executive dashboards to detailed views. • Collaborate with analytics and business teams to support reporting, forecasting, and AI-driven initiatives. • Ensure data solutions are scalable, performant, and aligned with best practices in data architecture. Qualifications: How much experience must I have? You should have at least 5+ years of experience in data engineering or similar roles. • Strong experience in Data Engineering with hands-on expertise in SQL and Python. • Proven experience building ETL/ELT pipelines in cloud environments (Azure preferred). • Experience working with lakehouse architectures (e.g., Parquet on Azure Data Lake, Synapse, or similar). • Hands-on experience with tools such as Azure Data Factory, Synapse, Fabric, Airflow, or dbt. • Experience designing data models and pipelines for forecasting and customer retention/churn use cases. • Strong experience integrating data from multiple systems (ERP, CRM) and handling data standardization and entity resolution. • Solid understanding of data quality, validation frameworks, and monitoring practices. • Experience designing data models for BI tools such as Power BI or similar. • Ability to work independently and collaborate with cross-functional teams in a fast-paced environment. What about languages? Advanced English level (written and spoken) is required for collaboration with cross-functional and client-facing teams. 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 we’ll explore working together!