Sr Data Engineer (LATAM Remote) at UP.Labs

United States

<h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Overview</strong></h3><div><span style="background-color: transparent; color: rgb(0, 0, 0);">UPLabs is a dynamic venture studio dedicated to building innovative startup companies from the ground up. Our team thrives on solving complex problems, driving technological advancements, and creating impactful digital products. We’re seeking a highly skilled professional to join our growing team and contribute to our mission of launching the next wave of AI powered solutions for enterprise customers</span></div><div><br></div><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Technical Challenge</strong></h3><div><span style="background-color: transparent; color: rgb(0, 0, 0);">Design, build, and evolve scalable data pipelines and data platforms to reliably power AI/ML models and agentic workflows for our customers. Partner closely with forward deployed product and engineering teams to translate ambiguous requirements into robust, maintainable data solutions.</span></div><h3><br></h3><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Responsibilities</strong></h3><ul><li class=""><span style="background-color: transparent;">Architect, build, and maintain scalable, production-grade data pipelines and data models to enable reliable ingestion, transformation, and delivery of data.</span></li><li class=""><span style="background-color: transparent;">Own end-to-end pipeline reliability, including orchestration, monitoring, alerting, and incident response to meet data freshness and quality expectations.</span></li><li class=""><span style="background-color: transparent;">Partner with product, engineering, and analytics stakeholders to define data requirements, translate them into clear technical specifications, and deliver iteratively.</span></li><li class=""><span style="background-color: transparent;">Improve performance, scalability, and cost efficiency of data workloads by tuning SQL queries, optimizing storage/compute patterns, and standardizing best practices across projects.</span></li><li class=""><span style="background-color: transparent;">Document data models, pipeline behavior, and operational runbooks to ensure maintainability and smooth knowledge transfer across accounts.</span></li></ul><div><br></div><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Required Skills</strong></h3><ul><li class=""><span style="background-color: transparent;">Strong data engineering expertise, including designing and operating data pipelines, data models, and batch/stream processing workflows in a production environment.</span></li><li class=""><span style="background-color: transparent;">Proficiency with Python for building data pipelines, automation, and data tooling.</span></li><li class=""><span style="background-color: transparent;">Advanced SQL skills for data transformation, analysis, and performance tuning.</span></li><li class=""><span style="background-color: transparent;">Experience working with PostgreSQL, including schema design, query optimization, and data integrity best practices.</span></li><li class=""><span style="background-color: transparent;">Experience building data pipelines and workloads on Databricks.</span></li><li class=""><span style="background-color: transparent;">Experience using dbt to develop, test, and maintain modular analytics engineering workflows.</span></li><li class=""><span style="background-color: transparent;">Experience working with MongoDB or other document databases as part of modern data stacks.</span></li><li class=""><span style="background-color: transparent;">Experience working with one or more major cloud platforms: AWS, Azure, or GCP.</span></li></ul><h3><br></h3><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Preferred Skills</strong></h3><ul><li class=""><span style="background-color: transparent;">Experience using Snowflake for cloud data warehousing, modeling, and analytics workloads.</span></li><li class=""><span style="background-color: transparent;">Working knowledge of Apache Spark for large-scale data processing.</span></li></ul><div><br></div><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">UPLabs Summary</strong></h3><div><span style="background-color: transparent; color: rgb(0, 0, 0);">We build high-growth technology startups that enable faster, cleaner, and safer movement of people and goods. Our vision is to transform the moving world by pairing leading corporations and entrepreneurs with a proven methodology for launching and scaling software and hardware companies.</span></div><div><span style="background-color: transparent; color: rgb(0, 0, 0);">We work with corporate investors over a multi-year period to launch a portfolio of mobility-focused ventures. Our team is dedicated to the first year of a new venture’s life cycle, from ideation to minimum viable product build (and beyond) to recruiting and hiring the full-time team who will scale the business.</span></div><div><br></div><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Location: </strong><span style="background-color: transparent; color: rgb(0, 0, 0);">LATAM Remote</span></h3><div><br></div><div style="text-align: justify;"><br></div>