Job summary Kiwibot is at the forefront of robotic delivery solutions, transforming urban logistics with autonomous technology. Our mission is to make last-mile delivery efficient, sustainable, and accessible. We are a data-driven company, and our Data Team is crucial to our success, enabling intelligent decision-making, optimizing robot performance, and supporting our rapid growth. Responsibilities - Design, develop, and maintain scalable, reliable, and efficient ETL/ELT pipelines for batch and real-time data processing (e.g., MQTT/Kafka data ingestion). - Manage and optimize our data warehousing solutions, primarily Google BigQuery, ensuring efficient data storage, querying, and cost-effectiveness. - Implement and maintain data quality assertions across all data pipelines to ensure data integrity from source to consumption. - Develop and integrate new data sources into our existing data ecosystem. - Troubleshoot and resolve data pipeline issues, ensuring minimal disruption to data availability. - Collaborate closely with company teams to understand their data needs and develop tailored data solutions. - Design and implement data workflows to support machine learning workflows - Contribute to the development of data-driven insights that improve robot autonomy and performance. - Contribute to the design and evolution of our overall data architecture, ensuring scalability, performance, and maintainability. - Implement and adhere to best practices for data modeling, schema design, and data governance. - Work with cloud infrastructure (GCP preferred) to deploy and manage data services. - Knowledge of spatial data wrangling and best practices for warehousing and consumption. - Develop and maintain monitoring solutions for data pipeline health and performance. - Ensure data consistency and accuracy in reporting tools. - Collaborate effectively with cross-functional teams to gather requirements and deliver data solutions. - Mentor junior team members and contribute to a culture of continuous learning and knowledge sharing within the data team. - Take ownership of projects from conception to deployment, ensuring timely and high-quality deliverables. Qualifications - Strong proficiency in Python for data engineering and scripting. - Extensive experience with SQL and relational databases (PostgreSQL preferred). - Proven expertise with Google Cloud Platform (GCP) services, especially BigQuery, Cloud Storage,, Cloud Functions. - Experience designing, building, and maintaining robust ETL/ELT data pipelines. - Familiarity with data orchestration tools (e.g., Apache Airflow,). - Experience with real-time data processing technologies (e.g., Kafka, MQTT). - Understanding of data modeling techniques (e.g., dimensional modeling, Kimball). - Familiarity with version control systems (Git/GitHub). - Exposure to AI/ML data pipelines and MLOps principles. - Knowledge of AI Agents for internal product development. - Familiarity with containerization technologies (Docker, Kubernetes). - Exposure to companies KPIs and OKRs among other performance metrics. Descripción del trabajo Lorem ipsum dolor sit amet , consectetur adipiscing elit. Nullam tempor vestibulum ex, eget consequat quam pellentesque vel. Etiam congue sed elit nec elementum. Morbi diam metus, rutrum id eleifend ac, porta in lectus. Sed scelerisque a augue et ornare. Donec lacinia nisi nec odio ultricies imperdiet. Morbi a dolor dignissim, tristique enim et, semper lacus. Morbi laoreet sollicitudin justo eget eleifend. Donec felis augue, accumsan in dapibus a, mattis sed ligula. Vestibulum at aliquet erat. Curabitur rhoncus urna vitae quam suscipit , at pulvinar turpis lacinia. Mauris magna sem, dignissim finibus fermentum ac, placerat at ex. Pellentesque aliquet, lorem pulvinar mollis ornare, orci turpis fermentum urna, non ullamcorper ligula enim a ante. Duis dolor est, consectetur ut sapien lacinia, tempor condimentum purus. Obtén acceso completo Accede a todos los puestos de alto nivel y consigue el trabajo de tus sueños. Inscríbete ahora