Data Engineer - CDI

Résumé du poste
CDI
Salaire : 60K à 73K €
Début : 02 mars 2025
Télétravail total
Expérience : > 5 ans
Compétences & expertises
Contenu généré
Gestion des tâches
Collaboration et travail d'équipe
Fivetran
Redis
Circleci
+15

BuyCo
BuyCo

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Le poste

Descriptif du poste

We are hiring a Data Engineer.

BuyCo is growing, and we are looking to strengthen the Data team, in order to keep a suitable workload for everyone.

You will join the Data team composed of 5 people: 

  • 🇫🇷Luc, Head of Data,

  • 🇺🇦🇸🇾Vadi & 🇫🇷Rodolphe, Data Analysts,

  • 🇮🇳Utpal, Data Scientist,

  • 🇫🇷Valentin, Data Product Manager intern.

You will report directly to Luc, and collaborate closely with cross-functional teams (Platform, Product, and Software Engineers mainly).

Our Technical Stack:

  • Infrastructure / DevOps: AWS, Linux, Kubernetes, Docker, CircleCI, Git/Github

  • Data: Power BI, Metabase, MageAI, DuckDB, Dremio, S3, PostgreSQL, Python, Parquet,

  • Frontend: React, TypeScript, GraphQL

  • Backend: Ruby (Rails), Go, RabbitMQ, PostgreSQL, Redis, Elasticsearch, S3

What you will do on a daily basis

Core tasks :

  • Design, build, and monitor robust data pipelines.

  • Overhaul and modernize our data stack, bringing a fresh perspective.

  • Facilitate seamless access to data and tools for the Data Team and beyond.

  • Audit existing systems, set up a roadmap, and execute operational improvements.

Your path at BuyCo

We imagine (ideally) a journey like this one:

- 4 months after your arrival: You met all the teams and stakeholders. The existing stack audit is done with the help of Luc & the team, and you established a roadmap. You gained mastery of current systems.

- 8 months after your arrival: You already achieved the first elements of your Data Engineering roadmap.

- 1 year after your arrival: You and the Data team achieved key milestones (implementing a new data warehouse, establishing continuous data replication, optimizing or challenging the use of Power BI) and deployed an innovative internal reporting solution.


Profil recherché

What BuyCo brings to the table

  • An immediate impact and responsibility on the Data stack of a fast growing startup.

  • Experience in the SaaS / LogTech ecosystem. If you share our enthusiasm for maritime transport / logistics, you will just love working here 🙏

  • A strategic role, acting as a pivot between your team members, but also other departments.

  • Working in an international context, collaborating internally with individuals from diverse backgrounds worldwide 🌐

The “ideal” profile we are looking for:

  • Strong experience with data warehouse technologies and analytical systems.

  • Proficiency in SQL, Python, and Public Cloud platforms (AWS preferred).

  • Familiarity with orchestration tools such as Airflow, Prefect, Dagster; ETL solutions: Airbyte, FiveTran or Mage AI.
    Also experience with Pandas, Polars, Ibis or DuckDB.

  • English speaker.

  • Open and collaborative, naturally reaching out to cross-functional teams.

Your profile will stand out if:

  • You speak English AND French. 

  • You have knowledge of data catalog tools, MLOps, and advanced reporting solutions (PowerBI alternatives).

  • You have a track record of projects in Change Data Capture (real-time database replication).

  • You are technologically curious and up-to-date on industry trends.

  • You are proactive and solutions-oriented with excellent organizational skills.

Compensation, location, remote and other details:

Compensation: between 60k and 73k per year.

Flexible remote work options: fully remote / hybrid remote / fully on-site, you choose!
As a reminder, we have offices in Marseille (HQ) and in Paris. 

+

(With a French contract)

Swile for meal vouchers

Health & Life Insurance: SideCare

Reimbursement of transport tickets

“Soft mobility” bonus

Incentive sharing scheme

Holiday bonus

Choice of hardware (Dell, Lenovo or Mac)

Reimbursement up to 300 euros for remote items


Déroulement des entretiens

Step 1: Interview with Cyril, Talent Acquisition Manager (30min)

Step 2: Technical interview focusing on architecture and declarative knowledge (45 min).

Step 3: Hands-on use case interview with the Data Team (1 hour).

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