Principal Engineer, Data Platform New Remote - United States

AlphaSense, Inc.; United States; Remote; USD 246,000 - 339,000; Full time

Job summary

AlphaSense, Inc. is seeking an experienced Data Platform Engineer to help set the technical direction for our Data Platform and storage ecosystem.

You will design, build, and operate systems for large-scale data migrations across cells and geographies, ensuring minimal downtime and high reliability. You will work with Kubernetes-native infrastructure, managed services, and cross-functional teams to enable self-service storage for product teams, drive scalability improvements, and mentor senior

Qualifications

• Deep hands-on experience designing and operating data platforms and storage systems.
• Production scale experience with modern storage systems (MongoDB, ClickHouse, Redis, PostgreSQL).
• Cloud-native data storage experience on AWS and Kubernetes-based deployments.
• Experience with multi-tenant, multi-region architectures and data migrations.
• Ability to design and ship platforms and tooling used by other engineers.

Responsibilities

• Help set architecture and roadmap for the Data Platform and storage ecosystem.
• Build capabilities for large-scale data migrations across cells, regions, and geographies with minimal downtime.
• Enable product teams to self-provision, operate, and scale storage.
• Drive data-layer changes required by cell-based architecture, including data placement and replication.
• Define a managed-first approach and balance self-managed vs. managed services where appropriate.
• Identify and close scalability gaps in data stores across regions and deployments.
• Build shared libraries to empower product teams with self-service storage capabilities.
• Collaborate with Cloud Platform, SRE, and DevEx teams; mentor Staff and Senior engineers.
• Apply AI tooling to data platform work for tasks like slow query reviews and incident diagnosis.

Skills

Data platform design

Kubernetes & containers

Multi-region architectures

Large-scale data migrations

Self-service storage enablement

Tools

MongoDB

ClickHouse

Redis

PostgreSQL

Kafka

Temporal

Vespa

Job description

AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster, more confident decisions in business and finance. The platform combines domain-specific AI with a vast content universe of over 500 million premium business documents — including equity research, earnings calls, expert interviews, filings, news, and internal proprietary content. Purpose-built for speed, accuracy, and enterprise-grade security, AlphaSense helps teams extract critical insights, uncover market-moving trends, and automate complex workflows with high-quality outputs. With AI solutions like Generative Search, Generative Grid, and Deep Research, AlphaSense delivers the clarity and depth professionals need to navigate complexity and obtain accurate, real-time information quickly. For more information, visit www.alpha-sense.com . Come join us.

About the Role:

AlphaSense runs a large-scale, Kubernetes-native platform built on a modern microservices architecture, serving the majority of the Fortune 500. We are moving it to a cell-based architecture, where each cell is an independent deployment of the platform.

The hardest part is data. Our platform relies on a broad ecosystem of data platforms and storage systems, including Vespa, MongoDB, ClickHouse, Redis, ScyllaDB, PostgreSQL, Temporal, and Kafka, to name a few. This role is focused on the Data Platform: the capabilities that let engineering teams build, run, and scale their storage at large scale without each team becoming an expert in every system.

You will help set the technical direction for the Data Platform and build it rather than only specify it. A central part of the work is building the capabilities for large-scale data migrations, so we can create, move, split, and rebalance data across cells and geographies as the cell-based architecture rolls out.

We prefer managed solutions over self-hosted ones, and we expect engineers to own their storage. Teams run what they build, and this role makes that model work at scale: you build it, you run it, and you scale it. Your job is to give teams the platform, standards, and tooling to do that safely, and to own the reliability and scalability of the platform itself.

Responsibilities:

• Help set the architecture and roadmap for the Data Platform and the storage ecosystem behind it
• Build the capabilities for large-scale data migrations across cells, regions, and geographies, including tooling for moving, splitting, validating, and rolling back data with minimal downtime
• Enable product teams self-service ways to provision, operate, and scale their own storage
• Drive the data-layer changes that cell-based architecture requires, including data placement, tenant routing, replication, and isolation
• Define and apply the managed-first approach: choose managed services where they fit, and build and run self-managed systems only where there is a clear reason
• Find and close scalability gaps in data stores across regions, cells and deployment models
• Build shared libraries that give product teams self-service storage capabilities
• Closely partner with Cloud Platform, SRE, and DevEx teams
• Raise the architectural bar across the organization and mentor Staff and Senior engineers
• Apply AI tooling to data platform work, such as slow query reviews and incident diagnosis

Requirements:

• Deep hands-on experience designing and operating data platforms and storage systems
• Production large-scale experience with storages (e.g. MongoDB, ClickHouse, Redis, PostgreSQL)
• Cloud-native data storage experience, including managed data services on AWS
• Strong background in Kubernetes and containers
• Track record of designing and running large-scale data migrations, including live migrations
• Experience with cell-based, multi-tenant or multi-region architectures
• Experience building platforms and tooling that other engineers use, and comfort with a model where engineers own their storage and run what they build
• Demonstrated ability to land significant changes in code owned by other teams
• A record of spotting data scalability and reliability limits before they turn into incidents
• Ability and desire to design, lead, influence, and deliver on ambitious technical roadmaps

Nice to have:

• Experience running storage systems on top of Kubernetes
• Experience building control planes with Crossplane
• Experience with private, isolated, on-premises, or air-gapped deployments

For base compensation, we set standard ranges for all roles based on function and level benchmarked against similar stage growth companies and internal comparables. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors including candidate experience/expertise and may vary from the amounts listed below.

You may also be offered a performance-based bonus, equity, and a generous benefits program.

Base Compensation Range

$246,000 - $339,000 USD

AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination.

In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works.

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in AlphaSense’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:

A \"disabled veteran\" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A \"recently separated veteran\" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An \"active duty wartime or campaign badge veteran\" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An \"Armed forces service medal veteran\" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.