Data Engineer (Tech-lead)

Job description

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer (Tech-Lead) based in Brazil.** This is a full-time contractor opportunity for an experienced Data Engineer ready to combine hands-on engineering with technical leadership. You will architect and scale robust data ecosystems, transforming complex data sources into reliable, production-ready pipelines and actionable insights. The role spans data architecture, transformation, orchestration, infrastructure, DevOps, and end-to-end product delivery. You will work with modern technologies including Snowflake, dbt, Apache Airflow, Python, SQL, Docker, Kubernetes, and GitLab CI/CD. Beyond technical execution, you will guide engineering practices and help ensure consistency, scalability, reliability, and maintainability across the data platform. Working remotely with international teams, you will collaborate primarily during Central Time business hours and operate in an English-first environment. ### Accountabilities: - Design and architect scalable, reliable, and high-quality data systems and end-to-end pipelines following modern engineering standards and best practices. - Lead the development of complex data models and transformation workflows using Snowflake and dbt. - Design, implement, and optimize Apache Airflow workflows to orchestrate sophisticated data pipelines and manage complex dependencies. - Establish reliable infrastructure and deployment practices using Docker, Kubernetes, and GitLab CI/CD. - Take ownership of the complete data product lifecycle, from architecture and initial development through deployment, production operation, and continuous improvement. - Develop and maintain robust data processing and automation solutions using Python, SQL, and Bash. - Provide technical leadership, mentorship, and guidance to engineering team members, promoting strong development standards and engineering practices. - Drive technical decision-making around architecture, scalability, reliability, maintainability, and production readiness. - Collaborate closely with distributed technical and product teams to translate requirements into effective data solutions. - Ensure data systems and products are delivered efficiently, reliably, and in alignment with broader project objectives. - Participate in technical ceremonies, stand-ups, architecture discussions, and collaborative sessions during overlapping Central Time business hours. ### Requirements - Advanced proficiency in Python, SQL, and Bash, with the ability to apply these technologies to complex data processing, automation, and engineering challenges. - Deep hands-on experience with Snowflake as a primary cloud data warehouse. - Strong experience with dbt for data modeling, transformation, testing, and maintainable analytics engineering workflows. - Practical expertise with Apache Airflow for designing, orchestrating, monitoring, and troubleshooting complex data workflows. - Solid DevOps experience with Docker, Kubernetes, and GitLab CI/CD, including containerization, deployment automation, and environment consistency. - Proven experience in data system architecture, with the ability to design scalable and production-ready data ecosystems. - Previous experience leading or managing technical teams, providing mentorship and establishing engineering best practices. - Strong understanding of the complete data product lifecycle, from initial architecture through production deployment and ongoing improvement. - Excellent analytical and problem-solving abilities, with a structured approach to complex technical challenges. - Strong communication and collaboration skills, particularly in distributed and cross-functional teams. - Fluent English, with excellent written and verbal communication skills for interviews, technical documentation, daily collaboration, and team leadership. - Experience building interactive data applications or dashboards with Streamlit is a plus. - Experience designing automated data validation and data quality systems is desirable. - Demonstrated success in shipping multiple data-centric products in fast-paced environments is an advantage. - Availability to work remotely from Brazil with consistent overlap with Central Time (CST/CDT), including key meetings, stand-ups, and collaborative sessions. ### Benefits - Fully remote work from Brazil as part of an international LATAM-based team. - Full-time contractor engagement with exposure to international technology projects and distributed engineering teams. - Opportunity to take on a high-impact technical leadership role across architecture, data engineering, DevOps, and product delivery. - Hands-on work with modern data technologies including Snowflake, dbt, Apache Airflow, Docker, Kubernetes, and GitLab CI/CD. - High level of technical ownership over the design, development, and production delivery of data products. - Opportunity to collaborate with diverse international teams and solve complex data engineering challenges. - Professional growth through technical leadership, architecture ownership, and exposure to modern data and cloud engineering practices. - Remote collaboration aligned with Central Time business hours, providing structured overlap with international teams. - Compensation and contractor terms are determined according to the applicable engagement agreement and discussed during the recruitment process.