[Hiring] Staff Data Engineer @Robots and Pencils

Role Description

We’re looking for a Staff Data Engineer to join a multi-disciplinary engineering team building modern, enterprise-grade data platforms. This role is ideal for an experienced engineer who can define data strategy, own platform decisions end-to-end, and contribute to technical leadership across the team.

In this role, you will:

• Design scalable data lakes, warehouses, and pipelines.
• Define governance and quality standards.
• Drive data platform modernization across real, in-flight work where performance, reliability, and security are critical.
• Mentor more junior engineers.
• Partner with leadership on data strategy.
• Bring an AI-forward mindset.

What You’ll Do

Craft & Delivery

• 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.

Collaboration & Communication

• 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.

Leadership & Influence

• 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.

Qualifications

• 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.

Helpful Extras and Unique Skills

• A doer who sees something broken and fixes it.
• A fast learner who embraces the ever-changing AI landscape.
• Direct in a way that improves work quality.
• Obsessed with craft and detail.
• Built for ownership, honoring commitments and backing teammates.
• Resourceful when faced with constraints.
• Glad to collaborate with others who care deeply about their work.