Principal Data Engineer (Global)

Data Engineer, Principal

LOCATION: Worldwide (Remote-first / Hybrid optional)

REPORTS-TO: Software Engineering, Director

Data Engineer, Principal

CINC Systems

CINC Systems is the leading provider of accounting and management software for the community association management industry. Our platform powers more than 50,000 associations and millions of homes, connecting property managers, boards, and residents through secure, reliable, and intelligent technology.

The systems we build are increasingly complex and interconnected. Success in this environment is not defined only by writing correct code or building pipelines quickly. It requires system design, judgment, orchestration, and craftsmanship. The engineers who make the biggest difference create multiplier effects for their teams. They design data systems that are trustworthy, reliable, and capable of powering intelligent software.

As we modernize the platform into an AI enabled ecosystem, data engineering plays a central role. Reliable, well designed data systems are the foundation of automation, analytics, and applied AI across the product.

Role Overview

We are hiring a Principal Data Engineer to lead and build a high performing data engineering team responsible for core data infrastructure within the CINC platform.

This is a practical, hands on leadership role. Principals at CINC are both technical experts and team leaders. You will guide the engineering direction of a team, recruit and mentor strong engineers, and design the systems that enable reliable, high quality data across the platform.

This role sits at the intersection of data engineering, platform architecture, and applied AI. You will help design the pipelines, streaming systems, and data models that power analytics, automation, and intelligent applications.

Key Responsibilities

As a Principal Engineer you will lead a small team responsible for a critical portion of the data platform. Your work combines leadership, architecture, and hands on engineering.

You will guide the design and implementation of scalable data systems that connect transactional services, analytics platforms, and AI enabled applications. These systems must operate reliably inside a large production environment and integrate cleanly with microservices and event driven architectures across the platform.

You will also play a key role in developing the data engineering discipline within the organization. Principals create environments where great engineering work can emerge. That includes supporting highly skilled engineers, collaborating with AI and product teams, and establishing patterns that make data reliable and accessible.

In this role you will:

• Lead the technical direction of a data engineering team in partnership with product and platform leaders

• Design and build scalable, event driven data pipelines and platform services

• Architect data models and infrastructure that support analytics, operational systems, and AI applications

• Work closely with AI engineers and application teams to ensure data is structured for intelligent applications

• Mentor engineers and raise the overall standard for data engineering craftsmanship

• Contribute to architectural patterns and engineering practices across the organization

Qualifications

You are an experienced engineer who enjoys designing complex systems and helping teams succeed. You have significant experience building large scale data infrastructure and care deeply about how data systems are designed and operated.

Most importantly, you think in systems rather than pipelines. You understand how data architecture, application architecture, and organizational design interact over time.

Experience with practices such as Extreme Programming, continuous delivery, automated testing, and trunk based development is a strong advantage. These disciplines are especially valuable when building data platforms that must evolve quickly while maintaining reliability.

Strong candidates typically bring:

Core Technical Expertise

• 12 or more years of experience in data engineering or backend software engineering

• Deep expertise designing large scale data pipelines and distributed data systems

• Advanced SQL skills and strong programming ability in languages such as Python

• Experience building event driven data architectures using modern cloud services (AWS preferred)

• Strong knowledge of relational and analytical data platforms

• Experience designing data models and data contracts for microservices architectures

• Familiarity with streaming architectures and real time data pipelines

• Solid Software Engineering fundamentals including API design, microservices, and system integration patterns (e.g. service mesh, api gateway, event-driven)

• Practical experience with cloud-native environments (AWS, GCP, or equivalent), including serverless compute and containerized deployments

Leadership and Collaboration

• Demonstrated ability to lead through influence, setting direction and raising standards for quality and maintainability

• Skilled in communicating complex trade-offs and design decisions clearly to both technical and non-technical audiences

• Experience leading other highly-skilled engineers and contributing to architectural strategy

• Strong sense of ownership, curiosity, and ability to deliver in a fast-moving, global environment

• Strategic thinker capable of evaluating build versus buy decisions with long-term organizational impact in mind

AI and Intelligent Systems

• Experience supporting AI enabled products by building reliable training and inference data pipelines

• Familiarity with vector databases, embeddings, and retrieval systems used in modern AI architectures

• Understanding of how data quality, lineage, and architecture affect AI outcomes and product experiences

Mindset and Values

• Builder’s mindset with comfort in ambiguity and a focus on delivering outcomes

• Clear communicator who can bridge technical and product conversations with credibility and empathy

• Learning-first attitude with curiosity about emerging models, frameworks, and best practices

• Values craftsmanship and continuous improvement in code quality, performance, and user experience

• Believes in collaboration, knowledge sharing, and elevating others through mentorship

What Success Looks Like

• The data platform becomes a reliable foundation for analytics, automation, and applied AI across the CINC ecosystem. Data pipelines are observable, resilient, and scalable. Product and AI teams can access clean, well structured data with minimal friction.

• Engineering teams adopt shared patterns for data architecture that improve reliability and speed of development.

• The Principal Data Engineer is recognized as both a technical leader and a multiplier who improves the systems, the people, and the overall engineering discipline.

• This role extends the leadership model, combining hands on engineering with team leadership and architectural responsibility.

• The Principal Data Engineer provides the foundation by building robust pipelines and infrastructure that power analytics and intelligent applications across the platform