Home › Companies › Profound › Data Engineer
Data Engineer
Profound · New York, New York · On Site · Active · Ashby
Job facts
| Field | Value |
|---|---|
| Company | Profound |
| Title | Data Engineer |
| Normalized title | - |
| Department / team | Data / Data |
| Location | New York, NY, United States |
| Work model | On Site |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-05-31 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Profound. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York. | Open |
| Department jobs | Active postings in Data. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Profound |
| Source | a38af73e-28ac-4547-a8d0-a912e857358f |
| ATS provider | Ashby |
Description
Profound is the marketing platform for the AI era. As people increasingly turn to ChatGPT, Perplexity, and Gemini to decide what to buy, we give brands the intelligence to see how AI represents them and the Agents to act on it. Today, ~13% of the Fortune 500, plus companies like Ramp, Figma, Chime, Calendly, and DocuSign, use Profound to turn AI Search from a black box into a measurable growth channel.
Backed by Lightspeed, Sequoia, Kleiner Perkins, and Khosla Ventures at a $1B valuation, we're a lean, fast-moving team across NYC, SF, Buenos Aires, and London, shipping at a relentless pace and defining a new category at the biggest shift in marketing in 25 years. If you want to do the best work of your career at the frontier of AI, come build it with us.
We are looking for an experienced Data Engineer to own and scale our data platform. You will maintain and optimize our pipelines, design new ingestion processes, and support the data needs of our product, data science, and go-to-market teams.
This is a great opportunity for someone who enjoys working with modern data tooling, improving performance and reliability, and building the foundation for machine learning-powered features.
What you’ll do Maintain and improve data pipelines to keep data flowing reliably from ingestion to delivery
Optimize performance and costs across Snowflake, Clickhouse, AWS, dbt, and Dagster
Own data quality by implementing monitoring, alerting, and validation
Manage and extend infrastructure, including orchestration and CI or CD for data workflows
Support MLOps as machine learning models are developed and productionized
Be on call for critical pipelines and respond quickly to issues
Collaborate with data scientists, product managers, and engineers to launch new data products
Who you are Proven experience designing, building, and maintaining production data pipelines
Proficiency in Python and SQL
Hands-on experience with dbt, orchestration frameworks such as Dagster, Airflow, or Prefect, and AWS
Familiarity with Snowflake, Clickhouse, or other modern data warehouses
Strong problem-solving skills and a proactive mindset
Experience with or interest in MLOps and supporting machine learning workflows in production
Strong sense of ownership and accountability for data quality and reliability
Motivated by access to rare and interesting AI data based on real human interactions with large language models
Excited by the opportunity to own and shape Profound’s data platform at an early stage
Interested in working on meaningful problems at the intersection of AI and marketing
Comfortable in a fast-moving culture with autonomy, trust, and room to grow
Drawn to competitive compensation and meaningful equity
Location This is an on-site role based in our Union Square, NYC office, designed for builders who thrive on speed, iteration, and meaningful impact.
For this role, the expected base salary range is $140,000 to $260,000. Comp may vary by location. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring.
#LI-DNI
Note: All official communication from Profound will come from a @tryprofound.com email address. If you're contacted by anyone using a different domain, please disregard and report it as spam.
Full job record
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| Source ID | a38af73e-28ac-4547-a8d0-a912e857358f |
| Board ID | a38af73e-28ac-4547-a8d0-a912e857358f |
| Provider | ashby |
| Provider Job Key | ea59c604-3a7d-445a-8a37-23252e240031 |
| Title | Data Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | New York, New York |
| Department | Data |
| Team | Data |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | United States |
| Region | NY |
| City | New York |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/Profound/ea59c604-3a7d-445a-8a37-23252e240031 |
| Apply URL | https://jobs.ashbyhq.com/Profound/ea59c604-3a7d-445a-8a37-23252e240031/application |
| First Seen At | 2026-05-29 07:13:08Z |
| Last Seen At | 2026-06-06 09:19:41Z |
| Last Checked At | 2026-06-06 09:19:41Z |
| Last Changed At | 2026-05-31 13:48:21Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=Profound/date=2026-06-06/2026-06-06T09-18-50-233Z-69cd64dd75ff3efcb94499eb5a7887aac070bd01a3dcd8008779785214f6cbe8.json |
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