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. The Opportunity: - Data Pipeline Development & Management: - 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. - Data Support: - 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. - Data Architecture & Infrastructure: - 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. - Monitoring, Reporting & Dashboards: - Develop and maintain monitoring solutions for data pipeline health and performance. - Team Collaboration & Leadership: - 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. Technical Skills & Qualifications: - Required: - Strong proficiency in Python for data engineering and scripting. - Extensive experience with SQL and relational databases. - Proven expertise with Google Cloud Platform services, especially BigQuery, Cloud Storage, Cloud Functions. - Experience designing, building, and maintaining robust ETL/ELT data pipelines.