Senior Data Engineer

Company Overview

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 Senior Data Engineer to design, build, and operate the data pipelines and platforms that power analytics, AI, and product work. This role is ideal for an engineer with several years of experience who can confidently own pipelines end-to-end and bring strong technical judgment to the problems they take on.

In this role, you will work as a key contributor on a cross-functional team, designing scalable pipelines, building and managing data warehouses and data lakes, and integrating data from across systems. You’ll collaborate with experienced engineers to enhance existing systems, deliver new capabilities, and contribute to the technical decisions that shape how our data work scales over time.

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

• Design and implement scalable data pipelines, taking ownership of features end-to-end

• Build and manage data warehouses and data lakes

• Optimize data processing workflows and integrate data from multiple systems

• Implement data modeling and schema design that supports analytics and downstream use

• Implement data validation and monitoring to ensure data quality, reliability, and availability

• Design and build data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows

• Bring an AI-forward coding mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace

Collaboration & Communication

• Collaborate closely with analytics, AI, and product teams to align data work with broader product and business goals

• Communicate technical tradeoffs and decisions clearly across functions, translating data architecture and constraints into terms others can act on

• Participate actively in code reviews and design discussions, raising concerns and offering constructive feedback

Leadership & Influence

• Contribute to data architecture decisions, bringing thoughtful perspective on tradeoffs and long-term implications

• Take ownership of meaningful pieces of work and follow through end-to-end, including the unglamorous parts of operating data systems

• Support data governance and compliance efforts, helping raise the bar on practices across the team

What You’ll Bring

• 5–7 years of professional data engineering experience

• Strong SQL and Python or Scala skills

• Working knowledge of cloud data platforms and enterprise data warehousing

• Hands-on experience with ETL/ELT frameworks and pipeline orchestration

• Experience with streaming platforms and real-time data processing

• Strong data modeling skills, including warehouse and lake schema design and data transformation

• Working knowledge of distributed systems

• Experience with data validation, quality, and observability

• Experience with CI/CD for data systems and container orchestration
  
  
• Experience building data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows
  
  
• Demonstrable, day-to-day usage of AI-forward coding tools such as Claude and Cursor
  
  
• Strong problem-solving skills and the ability to navigate ambiguous technical challenges with sound judgment
  
  
• Exposure to data mesh, data fabric, MLOps, or BI tool integration is a plus
  

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.
  
  
• Calm when it gets hot. When scope, timeline, and stakeholders pull in three directions, you slow the room down enough to make the right call. You’d rather raise the hard trade-off in week two than absorb it in week eight.
  
  
• 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.

We Offer

• 20 days of paid vacation.
• 15 days of unpaid vacation.
• All official public holidays off.
• 5 paid sick days without a doctor's certificate.
• Medical insurance.
• Military draft deferment (reservation) support.
• Cooperation under a gig-contract.