Lead Data Engineer (H/F/X) - CDI - Paris

12 Months ago • 5 Years + • Data Analysis

Job Summary

Job Description

Lead Data Engineer in Paris, build and maintain data pipelines, experience with GCP and Kubernetes, strong SQL & Python skills.
Must have:
  • Data Engineering
  • Google Cloud
  • SQL Experience
  • Python Expertise
Good to have:
  • RDBMS Experience
  • Kubernetes Skills
  • Data Modeling
  • Cloud Composer
Perks:
  • Startup Environment
  • Growth Opportunities

Job Details

About the job

At Le Collectionist, the purpose of the Data Team is to enable the company to operate at a high level of performance and efficiency with the power of Data.

We are doing that by focusing on 3 key missions:

  • Providing trusted and reliable Data products and insights to help the company achieve its goals
  • Empowering people to use Data autonomously to minimize time from question to insight to action
  • Bringing innovative Data capabilities to explore new business opportunities

The Data team is composed of 3 Data Analysts (including 1 intern), 1 Data Engineer and is led by the Head of Data. The team is part of the Tech & Product department and reports to the CTPO.

The team works as a service-oriented team for now but we are trying to shift step-by-step to a more product-oriented team delivering data assets and tools that will allow people to use data autonomously and why not explore AI/ML projects in the future.

The Data Engineer is responsible for the company’s Data Platform: from the infrastructure setup to the release and management of the Warehouse trusted data model.

As of today, this Data Platform is mainly used for Analytics & BI use cases to help teams work more efficiently and make better decisions by providing a consolidated view of LC business performance through dashboards and analysis.

By joining us, you will be part of a Data team that, while still in its early stages of development, made the effort of building a strong basis and setting up a lot of best practices.

It will be the opportunity for you to bring what you have learned to help us fulfill our purpose, improve the impact of the Data in the company and be a key driver of the Data team’s development.

🚀 Key missions

As a Lead Data Engineer, you will report directly to the Head of Data and will be responsible for:

  • Building and maintaining data ingestion and processing pipelines (cleaning, curation, data quality checks, etc.)
  • Providing and maintaining consumption-ready trusted core data sets for Data Analysts or Business users
  • Deploying, monitoring and optimizing components of the Data Platform
  • Providing and maintaining tools for Data Analysts
  • Writing and maintaining the Data Platform documentation
  • Managing and coaching the Data Engineers (1 for now)

At LC, the Data Engineer role has a mix of Data Platform Engineer and Analytics Engineer responsibilities.

🏭 Our technical stack

  • Cloud provider: Google Cloud Platform
  • Data Warehouse: BigQuery
  • Ingestion tool: Airbyte (self-hosted, on Kubernetes)
  • Orchestration & Transformation: Cloud Composer (Apache Airflow), Dataform
  • BI tool: Looker Studio
  • Infra-as-Code: Terraform, Terragrunt
  • Main coding language: Python, SQL

🧑‍💼 Recruitment process

  • HR call with Marianne (Talent Acquisition Specialist) (30min)
  • Home assignment
  • Interview with Alexandre KEO (Your manager) + debrief home assignment (2h)
  • Interview with Julien (CTPO) (1h)

🎓 Wanted profile

Preferred Background/experience

  • Bac+5 with specialization in Data
  • > 5 years of experience in Data or Analytics Engineering team
  • Experience managing junior profiles or interns
  • An experience in a startup/scaleup company

Hard Skills

  • Strong knowledge of Software and Data Engineering principles
  • Great data modeling skills
  • Good level using SQL
  • Experience with any RDBMS (PostgreSQL, MySQL, SQL Server, etc.)
  • Experience with Google Cloud Platform
  • Experience with Kubernetes
  • Good experience with git
  • Good level with Python and CLI

Soft Skills

  • Team player
  • Thorough and detail-oriented
  • Growth mindset
  • Caring and good at explaining
  • Strong interest in using best practices
  • Not afraid to talk to business people

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