Data Engineer

Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. They are seeking a Staff Data Engineer to join their multi-disciplinary engineering team, responsible for designing scalable data platforms and driving data strategy while mentoring junior engineers.

Responsibilities:

• 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
• Experience with handling and modeling data in the healthcare industry is a plus
• AWS certifications, like Certified Data Engineer – Associate, strongly preferred