Staff Data Engineer

Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients. We're all in on AWS, combining deep UX capability with senior engineering talent to get AI into production fast and keep it there.   We’ve earned the trust of leaders across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing and more, and earned a reputation as the nimble alternative to traditional global systems integrators. Founded in 2009, with delivery centers in Canada, the United States, Eastern Europe, and Latin America, we are smaller, faster, and more senior by design. Our teams average 15+ years of experience. We move fast, sweat the details, and build things that actually ship.  

Position Overview  

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, and drive data platform modernization across real, in-flight work where performance, reliability, and security are critical. You’ll mentor more junior engineers, partner with leadership on data strategy, and bring an AI-forward mindset.   

Why This Role Matters  

At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate.     Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on.  

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  

What  You’ll  Bring  

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  

You’ll  Do Well Here if You Are  

A doer.  You see something broken and fix it. You'd rather move on clarity than wait for certainty.  

A fast learner who knows you don't know everything.  The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.  

Direct in a way that makes the work better.  You give honest feedback. You'd rather have the hard conversation than blow smoke.  

Obsessed with craft.  You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.  

Built for ownership.  You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.  

All in.  You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.  

Resourceful when the budget, timeline, or team is tight.  Constraints don't slow you down. They sharpen you.  

Glad to be in the room with people who care as much as you do.  Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.