Data Engineer Lead

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.

The Data Engineer Lead is responsible for designing, developing, and supporting data solutions that enable reporting, business intelligence, and predictive analytics across the organization. The role includes modernizing recurring manual reports by converting Excel workbooks, manual data pulls, and repetitive processes into automated data pipelines and scalable BI solutions. In addition, the role is responsible for supporting the team's predictive model production processes, including model scoring, production data preparation, and ensuring reliable operational execution of analytical models. Responsibilities Design, develop, and maintain automated data pipelines and analytics solutions. Automate manual reporting processes and repetitive data workflows. Optimize SQL queries, data models, and processing performance. Support production data preparation and model scoring for predictive analytics. Monitor data quality, troubleshoot pipeline issues, and improve reliability. Collaborate with business and technical stakeholders to deliver scalable data solutions. Promote data engineering best practices and drive continuous improvements.

Required: Strong experience as a Data Engineer, Analytical Data Engineer, Analytics Engineer, BI Developer, Reporting Engineer, or similar role, with a proven track record of designing, automating, and delivering production reporting and analytics solutions. SQL Server and database expertise. Strong SQL Server development and database management skills, including writing complex queries, optimizing performance, and supporting production reporting and analytical workloads. Ability to translate ambiguous business questions into efficient SQL solutions using joins, window functions, CTEs, and sound data modeling principles. Programming and modern data platforms. Proficiency in Python for automation, data processing, and analytical workflows. Experience working with Databricks to develop, maintain, and support production data pipelines and analytics solutions. Business Intelligence development. Demonstrated experience developing reports and dashboards using Tableau or comparable BI tools. Ability to design reporting solutions that are actively used by the business and clearly communicate the purpose and value of each report. End to end automation. Experience taking recurring reporting processes from manual execution to automated production solutions. Comfortable determining when logic belongs in SQL, Python, or another appropriate technology to build scalable and maintainable data workflows. Predictive model production. Experience supporting predictive model production processes, including model scoring, production data preparation, workflow scheduling, monitoring, troubleshooting, and ensuring reliable operational execution of analytical models. Reverse engineering and reconciliation. Ability to interpret an undocumented Excel report, including its filters, joins, date logic, and business rules, and accurately reproduce it. A disciplined approach to reconciling output against a baseline until every discrepancy is explained. Communication with nontechnical stakeholders. Ability to elicit requirements and business rules from report owners who understand what they need but not how it is built. Preferred: Deep Tableau experience (strong report design in Power BI, Looker, or similar accepted) SQL Server or other Microsoft data platforms Experience with Databricks in production analytics environments Dimensional modeling, including reporting marts, conformed dimensions, and shared fact tables Experience modernizing a portfolio of legacy Excel reports Experience supporting predictive model production or machine learning operations in a production environment Experience in hospitality, vacation ownership, or operational reporting

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.