Lead Analytics Engineer

il y a 3 semaines

Paris, Île-de-France Fabulous Temps plein
About the Data Team

Join our dynamic data team at Fabulous, where we collaborate across various departments to drive data-informed decisions that enhance our business units, including Product Growth, User Acquisition, and Finance.

Our team focuses on three key areas:

  • Data Project Management: We prioritize and manage requests based on business needs, refining requirements and acceptance criteria with stakeholders. Our approach ensures effective communication and a robust feedback loop with all parties involved.
  • Applied Analytics & Data Science: We engage in data exploration and define agile analytics strategies. Our goal is to balance simplicity with complexity, ensuring that all new projects incorporate a strong Data Science element during their initial iterations.
  • Analytics Engineering: We specialize in data modeling and transformations to build, maintain, and scale our analytics pipelines. Once a project receives validation from stakeholders, we implement and enhance it iteratively within our dbt framework, emphasizing testing and data observability to manage technical debt effectively.

Every team member is expected to excel in at least two of these areas to contribute meaningfully and independently.

We operate in an agile environment, breaking larger projects into manageable iterations that typically last no longer than three weeks, ensuring impactful outcomes.

Our modern cloud-based data stack includes tools such as Fivetran, BigQuery, dbt, Amplitude, Metabase, and Looker Studio. We are looking for a well-rounded Lead Analytics Engineer who can seamlessly integrate into our agile context and deliver value promptly.

Responsibilities

This role is vital for the ongoing success of our data science initiatives:

  • Collaborate on data modeling and analytics engineering projects aimed at enhancing and maintaining our data models and analytics pipelines, working closely with the head of Data & Analytics.
  • Contribute to our codebase by building, testing, reviewing, and maintaining robust analytics pipelines using SQL and dbt, while also managing technical debt and improving engineering practices.
  • Gradually take ownership of specific aspects of the team's responsibilities, influencing the evolution of the analytics project's architecture and contributing to the team's growth.
  • Proactively engage in discussions to enhance team practices, cohesion, and overall impact.
  • Demonstrate autonomy and ownership in managing projects and stakeholders with minimal guidance.
  • Mentor junior team members and share knowledge to elevate the team's skill set.
  • Contribute to clear and concise functional documentation for future collaborators.
  • Hold a university degree in Engineering, Computer Science, or Applied Mathematics.
  • Possess a minimum of four years of experience in Data or Analytics Engineering.
  • Exhibit strong skills in data modeling and SQL, with experience in dbt or similar tools being advantageous.
  • Showcase excellent engineering skills, including testing, clean coding, peer reviewing, and familiarity with CI/CD and agile workflows.
  • Have prior experience with modern data stack tools and cloud-based data warehouses.
  • Demonstrate sound business acumen for effective project and stakeholder management.
  • Be a self-starter capable of working independently and fully owning projects.
  • Possess excellent written and verbal communication skills in English.
  • Be comfortable in a remote work environment.

Preferred Qualifications:

  • Familiarity with tools used in our data stack, such as Amplitude, dbt, BigQuery, and Metabase.
  • Strong analytical and statistical intuition.
  • Hands-on experience in data analysis.
  • Previous experience managing modern dbt data pipelines.
  • Experience in an agile startup environment.

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