Remote opportunity at
AlphaSensePrincipal Engineer, Data Platform
AlphaSense, an AI platform powering market intelligence and workflow orchestration for major business and financial organizations, seeks a Principal Engineer, Data Platform to join its team.…
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About This Role
AlphaSense, an AI platform powering market intelligence and workflow orchestration for major business and financial organizations, seeks a Principal Engineer, Data Platform to join its team. The company processes a vast repository of business documents to help professionals extract insights using advanced tools like Generative Search and Deep Research. This position centers on the company's data platform and underlying storage ecosystem, which utilizes technologies such as MongoDB, ClickHouse, Redis, PostgreSQL,…
Job Description
AlphaSense, an AI platform powering market intelligence and workflow orchestration for major business and financial organizations, seeks a Principal Engineer, Data Platform to join its team. The company processes a vast repository of business documents to help professionals extract insights using advanced tools like Generative Search and Deep Research.
This position centers on the company's data platform and underlying storage ecosystem, which utilizes technologies such as MongoDB, ClickHouse, Redis, PostgreSQL, Vespa, ScyllaDB, Temporal, and Kafka. The chosen candidate will guide technical strategy, build infrastructure rather than just write specifications, and spearhead large-scale data migrations to support a transition toward a cell-based architecture. Responsibilities include enabling self-service storage provisioning for product teams, ensuring operational reliability, defining managed-first standards, and mentoring senior and staff engineers.
The ideal applicant possesses extensive hands-on expertise with cloud-native data storage, Kubernetes, and large-scale live migrations. The role operates under a model where teams retain ownership of the storage solutions they construct.
Responsibilities
- Define the technical direction and roadmap for the Data Platform and its storage ecosystem
- Engineer capabilities for large-scale data migrations across cells, regions, and geographies
- Develop tooling to support data movement, splitting, validation, and rollbacks with minimal downtime
- Provide product teams with self-service mechanisms to provision, operate, and scale storage
- Implement data-layer modifications required for cell-based architecture, covering tenant routing, data placement, replication, and isolation
- Apply a managed-first philosophy by prioritizing managed services and building self-managed options only when necessary
- Identify and resolve scalability bottlenecks within data stores across various deployment models
- Construct shared libraries that offer self-service storage functionality to product teams
- Collaborate closely with Cloud Platform, DevEx, and SRE teams
- Elevate organizational architecture standards and mentor senior and staff level engineers
- Utilize AI tools for incident diagnosis and slow query reviews
Requirements
- Extensive hands-on background in designing and managing data platforms and storage systems
- Production-level experience with large-scale storage solutions such as ClickHouse, MongoDB, PostgreSQL, and Redis
- Familiarity with cloud-native data storage and managed data services on AWS
- Solid proficiency in containers and Kubernetes
- Demonstrated history of designing and executing large-scale, live data migrations
- Background working with multi-tenant, multi-region, or cell-based architectures
- Experience creating platforms and tooling utilized by other engineering teams
- Ability to introduce significant changes into codebases owned by other teams
- Track record of identifying data reliability and scalability limits prior to incidents
- Capacity to shape and deliver ambitious technical roadmaps
Qualifications
- Experience operating storage systems on top of Kubernetes
- Background building control planes utilizing Crossplane
- Familiarity with air-gapped, private, isolated, or on-premises deployments
Core Skills
Benefits
- Performance-based bonus
- Equity
- Comprehensive benefits program
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the salary range for the Principal Engineer, Data Platform role?
The base compensation range is $246,000 to $339,000 per year, with final offers determined by factors such as candidate expertise. Additional compensation may include equity, a performance-based bonus, and benefits.
What kind of architecture is AlphaSense implementing?
AlphaSense is transitioning its Kubernetes-native platform to a cell-based architecture where each cell operates as an independent deployment of the platform.
What storage technologies are used in the platform?
The platform relies on a wide ecosystem of storage systems and data platforms including MongoDB, ClickHouse, Redis, Vespa, ScyllaDB, PostgreSQL, Temporal, and Kafka.
Sample Interview Questions
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