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. Founded in 2009, we are smaller, faster, and more senior by design, with teams averaging 15+ years of experience.
Data Engineer
Location
United States
Posted
3 days ago
Salary
0
Seniority
Mid Level
Job Description
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 - Experience with handling and modeling data in the healthcare industry is a plus. - AWS certifications, like Certified Data Engineer – Associate, strongly preferred. Benefits - A doer who sees something broken and fixes it. - A fast learner who embraces the changing AI landscape. - Direct in a way that improves the work. - Obsessed with craft and detail. - Built for ownership and accountability. - All in for clients' businesses. - Resourceful under constraints. - Glad to collaborate with dedicated team members.
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Emmes GroupVeridix AI is the technology, data, and AI arm of the Emmes Group, a leading full-service contract research organization (CRO) with over 47 years of experience in supporting clinical research across more than 70 countries. With industry-leading capabilities in cell and gene therapy, vaccines, infectious diseases, and ophthalmology, Emmes is one of the top clinical service providers to the U.S. government and is rapidly expanding its presence in biopharma. Veridix AI develops advanced eClinical solutions, powering clinical trials through patient data collection, randomization, biospecimen tracking, and data quality monitoring. Our cutting-edge AI innovations, including Generative AI (GenAI) capabilities, are transforming clinical trial timelines by streamlining processes from document authoring to automating study builds. Our “Character Achieves Results” culture is driven by five key values that guide our actions in the way we conduct research and distinguish us as an organization: Integrity, Agility, Passion for Excellence, Collaborative Partnerships, and Intellectual Curiosity. If you share our motivations and passion in research, come join us!
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• Serve as the technical lead for the project—owning solution design decisions, guiding implementation standards, and mentoring other engineers through coaching, reviews, and knowledge sharing. • Design, develop, and maintain complex ETL pipelines using Databricks, ensuring scalable, high-performance data integration across multiple source systems. • Implement and optimize medallion architecture within Databricks, establishing clear data zones (raw, curated, trusted) to support governed, enterprise-wide reporting. • Develop and refine dimensional data models that enable unified, analytics-ready views of business domains and support automated dashboarding and KPI frameworks. • Collaborate closely with cross-functional teams (data stewards, IT, business stakeholders) to translate operational requirements into technical solutions, proactively clarifying dependencies and driving alignment. • Contribute to architectural decisions, leveraging your expertise to recommend best practices, challenge assumptions, and ensure data platform durability and flexibility. • Identify and address integration challenges, data quality issues, and process bottlenecks early, providing actionable insights and thoughtfully pushing back when project risks or inefficiencies arise. • Support knowledge transfer and documentation, empowering colleagues and clients to maintain and evolve data solutions independently.
