Data Lead

Resumen del puesto
Indefinido
Paris
Unos días en casa
Salario: No especificado
Competencias y conocimientos
Ingeniería de datos
Looker
Foundation
Metabase
BigQuery
+4

MakiPeople
MakiPeople

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El puesto

Descripción del puesto

About the Role

At Maki, data fuels everything: our AI agents, the user experience, customer insights, internal decision-making, and future predictive analytics.

We’re hiring our first data lead to own our data foundation and help shape how data becomes a product at Maki.

This is a builder role: you will architect systems, model data, expose insights, and infuse AI into how people interact with information.

You’ll work directly with Product, Engineering, and the Founders to lay the foundations of our long-term data strategy.

What You Will Do

Data Foundations

  • Design, build, and maintain data pipelines (ingestion → transformation → serving)

  • Own our data lake / warehouse and model production-grade tables

  • Implement monitoring, testing, documentation, and governance practices

Data Exposure & Insights

  • Own dashboarding (Looker, Metabase, or similar)

  • Deliver trustworthy datasets and self-serve analytics tools

  • Support customer SQL requests and internal ad-hoc analyses

  • Build the semantic layer that powers internal and external insights

Data as a Product

  • Build embedded data experiences inside Maki’s product

  • Explore and deploy AI-driven interfaces (natural language querying, automated reports)

  • Partner with the product team to turn raw data into customer value

What You Bring

  • Strong engineering foundation (software / data engineering)

  • Fluent SQL; Python experience is a plus

  • Experience with modern data stacks (BigQuery/Snowflake, dbt, Airflow)

  • Experience with BI tools (Looker, Metabase…)

  • Ability to design scalable models and pipelines

  • Curiosity for AI-driven analytics (LLMs, semantic layers, query generation)

  • Pragmatic, structured problem-solver

  • Comfortable with high ownership and ambiguity

Bonus Points

  • Experience building self-serve analytics tools

  • Past work on AI-based querying / Natural language to SQL

  • Experience embedding data products into SaaS applications

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