About Dolead

At Dolead, we align marketing, sales, and data to turn media investment into real pipeline. In short: we launch paid campaigns faster, integrate data with confidence, and deliver sales-ready leads at a fixed cost per lead.

Today, we support 200+ clients across 15 countries with a team of 70+ experts from 13 nationalities, split between offices in Paris, Madrid and Boston… and we keep growing !

The role

We’re looking for an Analytics Engineer to join our Data team and work closely with Thibault (Head of Data & Science).

You’ll sit at the intersection of data engineering and analytics: building reliable pipelines, enabling trusted reporting, and helping teams make faster, better decisions with data.

Typical split: ~60% engineering / 30% analytics enablement / 10% collaborative “science” projects.

What you’ll do

• Understand the system end-to-end: get a deep grasp of Dolead’s data flows, models, and architecture.
  Build and improve pipelines: maintain and optimize Python & SQL pipelines (with tools like Airbyte and dbt).

• Enable analytics at scale: contribute to our Looker / LookML stack (clean metrics, consistent definitions, reusable models).

• Work with the whole squad: collaborate daily with Data Analysts and Data Scientists, and partner with Tech & Product to ship data-driven features.

Raise data quality & reliability: improve monitoring, testing, documentation, version control/CI, data quality/observability.

Success in the first 3 months (what “good” looks like)

• You’ve mapped the key flows and models, and you can explain where the data comes from, how it transforms, and where it’s consumed.

• You’ve shipped improvements to the dbt layer (models + tests + docs) and removed at least one reliability pain point.

• You’ve contributed to a clearer Looker/LookML setup (metrics governance, consistency, usability) that makes reporting more trustworthy and faster.

Who we’re looking for

• 3+ years in Data Engineering / Analytics Engineering (or a closely related role).

• Strong SQL + Python skills and a pragmatic mindset (you ship, you iterate, you improve).

• Experience (or strong interest) in DBT and modern ELT stacks; Airbyte is a plus.

• Comfortable with BI/semantic layers (ideally Looker / LookML), and with aligning teams on metric definitions.

• Cloud familiarity: GCP / BigQuery is a plus.

• You’re used to working cross-functionally (Data, Product, Engineering) and translating business needs into reliable data products.

• Fluent in French and English.

No need to check every box. If the role feels like a strong match, apply, we’ll talk about it.

Read more about Dolead technical stack on https://stackshare.io/dolead/engineering

What we offer:

🤗 Healthcare: Sidecare — 100% covered by Dolead

💳 Lunch voucher: Swile — €9/day (50% covered)

🌴 Time off: 25 vacation days + 8 RTT

🌍 Multicultural environment: 13+ nationalities

🥳 Culture & events: monthly team & company moments

📍 Team hub: The team is anchored in Paris (Opéra), but we’re open to candidates based elsewhere if you can join key team moments in person from time to time.

Recruitment process:

• Screening call with Florian, Talent Acquisition Manager 

• Interview with the hiring manager Thibault 

• Use case (practical and time-boxed) with Thibault, Head of Data & Science (and relevant stakeholders)

• Final interview with Guillaume, CEO

Dolead wants to guarantee equality and an opportunity to all candidates. Therefore, all applications received are considered regardless of racial and ethnic origin, opinions or beliefs, gender, sexual orientation, health or disability.