Data Engineer

Perfume Specialists looking for their Data Engineer

We are a team of 5 people, bootstrapped and profitable. And we have access to more data on perfume than any other team in the world.

Sommelier du Parfum operates at the intersection of data and fragrance. We have built an ecosystem of products used by the biggest names in the sector:

• OmniScent : a consumer insights platform built on 7 million reviews analyzed through NLP, cross-referenced with market share data, social media analytics, olfactive classifications and proprietary sensory data. It is the compas used by top perfumer teams worldwide to guide their creative decisions.
• OmniPulse : a consumer testing platform that reinvents the testing experience (which is a prominent part of decision-making in fragrance).
• Sommelier du Parfum : a fragrance recommendation app with 200,000 users and a niche perfumery marketplace.

The role

You will be the person in charge of data engineering, which is an essential part of our trade. Your perimeter would be our entire data pipeline infrastructure which means you would not be yet another cog but an essential part of the organisation.

What you will be doing

• Build and make our ingestion pipelines reliable : consumer reviews (scraping, APIs, files), market share data, confidential sensory and olfactive data provided by our clients. Sources are heterogeneous, formats are unpredictable, and data freshness is critical to our commercial credibility.
• Set up a proper orchestrator (Prefect, Dagster, or Airflow — that's your call). Today, our data sourcing codebase isn't structured around reliable orchestration. That's both the problem and the opportunity.
• Build monitoring and alerting
• Work hand in hand with our ML Engineer (PhD in machine learning, research + DevOps profile) and with our CTO (Full-stack + DevOps profile) to ensure the data feeding our NLP models is clean, complete, and up to date.
• Scale our data infrastructure on AWS as the volume and number of clients grow.

What you won't have to do

• Reporting. Life's too short.
• Data science. Our ML Engineer handles that.
• Politics. There are 5 of us. Everyone talks to everyone.

Current stack

• Python (FastAPI)
• MongoDB
• AWS
• Orchestration: to be built : that's your playground

Who we're looking for

• 3 to 7 years of experience in data engineering, ideally in an environment where you were the only data engineer or part of a very small team.
• You've built end-to-end pipelines in production: ingestion, transformation, storage, monitoring. Not just consumed clean data that someone else prepared for you.
• You are comfortable with Python, MongoDB, and at least one modern orchestrator (Prefect, Dagster, or Airflow).
• You know how to deal with messy data, inconsistent formats, flaky third-party APIs, and Excel files sent by clients who consider them an "acceptable" exchange format.
• You're genuinely autonomous. Nobody will write your specs — we will discuss together the business problems and you will have to plan out a technical solution.
• You're fluent in English (it's our team's working language, both written and spoken).

What we offer

• Salary : €55–60K gross annual, depending on experience
• Equity : 0.3–0.4% of the company (4-year vesting, 1-year cliff) — everyone on the team is a shareholder
• Hybrid : office in Paris Montparnasse (Wojo), at least 2 days of remote work per week (we are flexible)
• Immediate impact: our platforms and data influence decision-making on roughly a third of the fragrances marketed worldwide
• A rare and impactful domain: we are fragrance specialists and are the best positioned team to better understand "taste" globally — not "yet another e-commerce Saas tool"

Hiring process

• 30-min call with the CEO — motivation, background, open conversation about the company
• 1-hour technical exchange — questions on approaches to real data engineering problems (no HR-style "3 strengths, 3 weaknesses" questions)
• 1-hour case study discussion with our CTO, CEO, and ML Engineer — based on a take-home exercise prepared in advance

Interested?

Apply here on Linkedin or write directly to with a few lines about what excites you and a link to your LinkedIn or GitHub. No need for a formal cover letter.