Principal Engineer, Data Platform

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Engineer, Data Platform based in the United States.

As Principal Engineer, Data Platform, you will shape the technical direction and build the capabilities behind a large-scale, cloud-native data ecosystem supporting a distributed microservices platform. You will play a pivotal role in the transition toward a cell-based architecture, enabling reliable data movement, isolation, and scalability across regions and geographies. Working across a diverse range of storage technologies, you will create shared platforms, tooling, and standards that empower engineering teams to manage their own data infrastructure. A major focus will be designing and delivering large-scale migrations with minimal downtime and strong safeguards. You will champion a managed-first approach while ensuring the reliability and performance of both managed and self-operated systems. This is a hands-on technical leadership position combining architecture, implementation, cross-functional influence, and mentorship. Accountabilities

• Define the architecture, technical standards, and long-term roadmap for the Data Platform and its storage ecosystem.

• Design and build capabilities for large-scale data migrations across cells, regions, and geographies, including tools for moving, splitting, validating, and rolling back data with minimal downtime.

• Develop self-service platforms, shared libraries, and tooling that allow product teams to provision, operate, and scale their own storage systems.

• Lead data-layer changes required by the cell-based architecture, including data placement, tenant routing, replication, and isolation.

• Establish and implement a managed-first strategy, selecting managed services where appropriate and operating self-managed systems when there is a clear technical need.

• Identify and address scalability, performance, and reliability limitations across data stores, regions, cells, and deployment models before they become incidents.

• Partner closely with Cloud Platform, Site Reliability Engineering (SRE), and Developer Experience (DevEx) teams to deliver reliable platform capabilities.

• Influence architectural decisions across the organization, raise engineering standards, and mentor Staff and Senior Engineers.

• Apply AI-powered tools to platform engineering workflows, including slow-query analysis and incident diagnosis.

Requirements:

• Extensive hands-on experience designing, building, and operating data platforms and large-scale storage systems.

• Proven production experience with technologies such as MongoDB, ClickHouse, Redis, and PostgreSQL.

• Strong understanding of cloud-native data storage, including managed data services on AWS.

• Advanced experience with Kubernetes, containers, and distributed systems.

• Demonstrated success designing and executing large-scale data migrations, particularly live migrations.

• Experience with cell-based, multi-tenant, or multi-region architectures.

• Background building internal platforms and developer tooling used by other engineering teams.

• Comfort with an engineering model in which teams own and operate the systems they build.

• Proven ability to deliver significant technical changes across codebases owned by other teams.

• Strong ability to anticipate data scalability and reliability constraints and address them proactively.

• Excellent technical leadership, communication, and collaboration skills, with the ability to influence stakeholders and drive ambitious technical roadmaps.

Nice to have:

• Experience operating storage systems on Kubernetes.

• Familiarity with building control planes using Crossplane.

• Experience supporting private, isolated, on-premises, or air-gapped deployments.

Benefits:

• Base salary: $246,000–$339,000 USD, depending on experience, expertise, and other relevant factors.

• Potential performance-based bonus.

• Equity opportunities.

• Generous employee benefits program.

• Remote position based in the United States.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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