Principal Data Engineer
Leads the design and operation of a cloud-native data platform for a healthcare analytics company, focusing on scalable infrastructure, data pipelines, and AI/ML enablement.
- Compensation
- Not disclosed
- Location
- Remote, India
- Work setup
- Remote
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 8+ years of experience in Data Engineering, Platform Engineering, Infrastructure Engineering, or related technical disciplines.
- Demonstrated expertise designing and implementing modern cloud-based data platforms.
- Strong hands-on experience with data warehousing, orchestration, transformation, and DevOps technologies.
- Experience building and optimizing large-scale data pipelines and data models.
- Deep understanding of software engineering principles, infrastructure automation, and production operations.
- Experience operating in highly regulated, compliance-sensitive, or enterprise environments.
- Proven track record of leading technical initiatives through influence rather than direct authority.
Nice to have
- Experience within healthcare, life sciences, pharmaceutical, or analytics organizations.
- Experience supporting AI/ML platforms, MLOps capabilities, feature stores, or model deployment frameworks.
- Familiarity with claims, formulary, commercial, or real-world evidence datasets.
- Experience leading enterprise-scale data migrations, modernization programs, or platform consolidations.
- Exposure to global engineering teams and distributed delivery models.
Full description
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.