Principal Engineer, Data Platform
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2d ago
The date the source published, not the day we noticed it (2026-10-30). Last seen at its source 3h ago.
We have tracked this listing since 30 Oct 2026 (2 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.
Is it remote?
Remote - United States
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$246k–339k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Greenhouse employer's own board first seen 2d ago · last seen 3h ago
The listing
About AlphaSense:
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.
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.
Recruiting Scams and Fraud
We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters. These scams may involve fake job offers, requests for sensitive personal information, or demands for payment. Please note:
- AlphaSense never asks candidates to pay for job applications, equipment, or training.
- All official communications will come from an @alpha-sense.com email address.
- If you’re unsure about a job posting or recruiter, verify it on our Careers page.
If you believe you’ve been targeted by a scam or have any doubts regarding the authenticity of any job listing purportedly from or on behalf of AlphaSense please contact us. Your security and trust matter to us.