We are building the Data Hub, a centralized data platform responsible for consolidating legacy data infrastructure, establishing enterprise-grade data foundations, and enabling advanced analytics and AI capabilities across Precision AQ.
The Principal Data Engineer is a senior technical leader and hands-on contributor responsible for the design, implementation, optimization, and operation of the Data Hub’s core platform capabilities. This role sits at the intersection of data engineering, platform engineering, DevOps, architecture, and data governance. You will help define the technical direction of the platform while remaining actively involved in designing solutions, building infrastructure, reviewing code, troubleshooting production issues, and improving engineering practices.
This is not a management role. While you will mentor and guide junior engineers, analytics engineers, and platform contributors, you will not have direct reports. We are looking for an experienced practitioner who enjoys solving complex technical challenges, setting high engineering standards, and leading through expertise and influence rather than organizational hierarchy.
As a member of the Data Hub leadership team, you will contribute to technology strategy, roadmap prioritization, architecture governance, vendor evaluation, and executive reporting while remaining deeply engaged in day-to-day engineering activities.
Main duties and responsibilities
Infrastructure and Platform Engineering
- Design, build, and maintain scalable, secure, and reliable cloud-native data platform infrastructure.
- Develop infrastructure-as-code, CI/CD pipelines, deployment automation, and environment management processes.
- Partner with Corporate IT, Security, and platform vendors to ensure compliance, reliability, and operational excellence.
- Improve platform observability through monitoring, alerting, logging, and performance tracking.
Data Architecture and Modelling
- Design scalable data models supporting analytics, reporting, AI/ML, and operational use cases.
- Define and evolve data architecture standards, patterns, and best practices across the Data Hub ecosystem.
- Ensure data solutions align with governance, lineage, security, and regulatory requirements.
- Guide engineering teams in implementing maintainable and extensible data structures.
Data Engineering and Solution Delivery
- Build and optimize data ingestion, transformation, and delivery pipelines across multiple business domains.
- Lead technical design reviews and contribute directly to implementation of complex data engineering initiatives.
- Collaborate with Product, Analytics, AI/ML, and business stakeholders to translate requirements into scalable technical solutions.
- Provide hands-on support for critical platform initiatives, migrations, and modernization programs.
DevOps and Engineering Excellence
- Establish and enforce software engineering, GitOps, DevOps, testing, and deployment standards.
- Drive automation across development, deployment, monitoring, and operational processes.
- Promote best practices for code quality, documentation, technical debt management, and release management.
- Conduct architecture reviews and code reviews to ensure consistency and maintainability.
Quality, Performance, and Reliability Optimization
- Identify and resolve performance bottlenecks across pipelines, databases, and infrastructure.
- Define and implement data quality frameworks, automated validation processes, and operational controls.
- Optimize platform cost, scalability, reliability, and processing efficiency.
- Lead root-cause analysi