Staff Data Engineer

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🕒 June 2

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Gugu Robotics

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🤖 Artificial Intelligence

🛍️ eCommerce

Artificial Intelligence • Robotics • eCommerce

Gugu Robotics is a pioneering startup based in West Africa, dedicated to harnessing the power of AI, robotics, and drone technology to create innovative solutions for various industries. Founded by visionary engineer Emmy Pencil, the company specializes in designing and building customized robotic systems, drones, and AI-enabled electric vehicles that address critical challenges across sectors such as agriculture, military, medical, and beyond. With a diverse team of experts, Gugu Robotics aims to redefine possibilities in automation and efficient energy solutions to shape the future of technology.

📋 Description

• Define data architecture and platform strategy, leading design across pipelines, warehouses, and data lakes • Build and optimize scalable data pipelines supporting batch and real-time processing • Define and enforce data governance, quality standards, and compliance frameworks across the platform • Build monitoring, logging, and alerting for data pipelines and services, and contribute to CI/CD workflows for data deployment and automation • Drive data platform modernization, optimizing for performance, cost, and scalability • Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace • Design and implement data contracts and event flows in collaboration with backend, platform, and engineering teams • Lead the design and implementation of data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows • Integrate data services with APIs, middleware, and third-party systems to support end-to-end data consumption • Partner with leadership on data strategy, translating technical depth into decisions others can act on • Collaborate closely with engineering, analytics, AI, and product teams to align data platforms with broader goals • Advocate for data quality, governance, and platform best practices across teams and engagements • Establish data engineering standards that lift the quality and consistency of work across the team • Mentor junior and mid-level engineers, helping them grow their craft, confidence, and impact • Make high-stakes architectural decisions with clear ownership and consideration of long-term tradeoffs

🎯 Requirements

• 7+ years of professional data engineering experience, with experience leading complex data platform initiatives • Strong system architecture background with expertise in distributed data systems • Expert proficiency in Python, Scala, and SQL • Deep expertise with cloud-native data platforms and enterprise data warehousing • Strong expertise in data pipeline orchestration and processing • Strong experience with streaming platforms and real-time data processing (e.g., Kafka, Kinesis, Pub/Sub) • Strong data modeling expertise and experience with data transformation • Strong experience with data quality, governance, and compliance frameworks • Strong experience with container orchestration and CI/CD for data systems • Strong experience building data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows • Demonstrated leadership and technical mentoring experience across a team or organization • Strong stakeholder communication skills, with the ability to translate technical depth across audiences • Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor • Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment • Experience with data mesh or data fabric concepts, lakehouse architectures, or governance framework implementation is a plus.

🏖️ Benefits

• Competitive salary • Flexible working hours • Professional development opportunities