Staff Data Engineer

Gugu Robotics

Staff Data Engineer leading design across data pipelines and modernizing data platforms at Robots and Pencils. Collaborate with cross-functional teams on data strategy and AI initiatives.

Posted 6/2/2026full-timeRemote • 🇨🇴 ColombiaLeadWebsite

Tech Stack

Tools & technologies

CloudKafkaPythonScalaSQL

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

Competitive salary
Flexible working hours
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data architecturedata pipelinesdata governancedata quality standardsCI/CDPythonScalaSQLdata modelingdata transformation

Soft Skills

leadershiptechnical mentoringstakeholder communicationproblem-solvingcollaboration