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Analytics Engineer

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Remote from
France
Salary
Undisclosed
Employment
Full Time
Experience
Director
Published
Apply before
29 Oct 2026
Listing views
28
Application actions
1
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AI Summary

The role, at a glance.

Alma is hiring an Analytics Engineer to strengthen a central data team supporting Finance, Product, Marketing, Risk, and Operations. The role focuses on transforming raw data into trusted, reusable datasets and semantic layers using dbt and BigQuery. Key responsibilities include data modeling, testing, documentation, lineage, governance, performance optimization, and removal of obsolete data assets. The engineer will mentor analysts, contribute to data-platform standards, and partner with technical and business stakeholders to enable reliable self-service analytics. This is a permanent full-time role based in Paris with hybrid work or remote work within France.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis role requires practical analytics engineering capability across dbt, dimensional modeling, data quality, governance, and cloud data tooling. It also carries substantial cross-functional and enablement responsibility, requiring the ability to set standards and translate technical data concepts for analysts and business stakeholders.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianHighly competitive
$115,000
US market range$90k–$140k
AI insightNo numeric salary is disclosed, so these are estimated US-market annual base-salary figures in USD for an Analytics Engineer with roughly 2+ years of relevant experience. Actual compensation for this France-based CDI role may differ materially based on local market practices, seniority, and total benefits.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you structure dbt models for a new business domain with raw source data and reporting requirements?

I would begin by documenting the source grain, primary keys, ownership, and important business definitions. I would create source definitions and staging models that standardize naming, types, and basic cleaning, then build intermediate models for reusable transformations and mart models at clear business grains. I would add tests for uniqueness, non-null keys, relationships, accepted values, and freshness, while documenting model purpose and lineage.

How do you ensure that a metric such as active customer is used consistently across Finance, Product, and Operations?

I would facilitate agreement on the business definition, including eligibility rules, time window, grain, exclusions, and source-of-truth data. I would encode the agreed definition in a governed semantic layer or reusable dbt model rather than allowing each team to recreate it. Documentation, ownership, version control, and stakeholder validation would make the metric discoverable and maintainable.

Describe how you would investigate a data-quality issue in a critical reporting table.

I would first assess the impact, identify when the issue began, and compare the affected model with upstream sources and recent code or schema changes. I would use dbt lineage, query-level validation, and model tests to isolate whether the cause is ingestion, transformation logic, a late-arriving source, or a changed business rule. After correcting the issue, I would communicate the impact clearly, backfill when needed, and add preventive tests or monitoring.

What approaches would you use to optimize an expensive or slow BigQuery transformation?

I would inspect the query plan and bytes scanned, then reduce unnecessary columns and repeated computation while filtering as early as appropriate. Depending on access patterns, I would use partitioning, clustering, incremental dbt models, and materialization choices that balance cost, freshness, and maintainability. I would validate that optimization preserves model grain, business logic, and downstream outputs before deployment.

How would you help data analysts adopt dbt and stronger governance practices?

I would provide practical templates, clear conventions, examples, and short training sessions centered on analysts' real workflows. Code reviews would be supportive and explain the reasoning behind tests, documentation, model layering, and pull-request practices. I would also collect feedback, reduce friction in the development process, and demonstrate how governed reusable assets improve trust and speed for analysts.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

🧡 About Alma

At Alma, we believe sustainable commerce depends on fair, well‑balanced trade. Because finance plays a pivotal role in business, our mission is to put it back in its rightful place – serving merchants and consumers. Our installment and deferred payment solutions help merchants boost sales by 20% or more, increase customer loyalty, and deliver a seamless shopping experience – without encouraging bad debt. As the buy now pay later leader in France and active in 10 European countries, we’ve empowered over +25,000 merchants and 10 million consumers. With 400+ Almakers and €100M+ ARR, Alma is scaling rapidly across Europe as a member of the Next40, and we’re just getting started!

👐 About the team

You will join Alma’s central Data team, which supports a wide range of business teams, including Finance, Product, Marketing, Risk, and Operations. The team is made up of six Data Analysts, including several experienced colleagues, and works at the intersection of Data Engineering, Data Analytics, and business teams.

Reporting to Gil Marlard, you will help strengthen the data foundations that support reporting, analytics, operational processes, and business decision-making.

This position is a permanent (CDI) role based in Paris, with a hybrid working model, we are also open to full remote in France.

💼 About the job

As an Analytics Engineer, you will help strengthen the data foundations that support the whole organization. The central Data team serves a wide range of business teams, including Finance, Product, Marketing, Risk, and Operations. You will join a team of six Data Analysts, including several experienced colleagues, and work at the intersection of Data Engineering, Data Analytics, and business teams.

You will transform raw data into trusted datasets that support reporting, analytics, operational processes, such as deciding which customer to call, and business decision-making.

Our data foundations currently have different levels of maturity across business teams, and part of our ambition is to rebuild and standardize some of them. Your work will be particularly important in enabling more self-service and conversational analytics for our business teams, by making data easier to find, understand, trust, and use.

A key part of your role will be improving the lineage and governance of our tables, following a medallion-inspired approach with clear layers.

Data modeling and data quality

  • Build and maintain reusable data models, macros, and semantic layers in dbt and BigQuery

  • Develop staging, intermediate, and mart models following clear data modeling principles

  • Implement data quality tests, freshness checks, and documentation

  • Improve the lineage, ownership, and discoverability of our most important tables

  • Strengthen our semantic layer and ensure that metric definitions are consistent

  • Identify and remove duplicated, obsolete, or deprecated datasets and content

  • Optimize queries and models for reliability, performance, and cost

Central Data Analytics Community

  • Build reusable data assets that can be leveraged by Data Analysts across different business domains

  • Lead enablement by mentoring analysts and training them on dbt, Looker, governance, and metric definitions

  • Partner on the data platform roadmap across GCP, BigQuery, Argo, dbt, and Looker

  • Contribute to keeping our data stack clean, reliable, and easy to maintain

  • Participate in code reviews and help define analytics engineering standards

  • Discuss and validate data contracts with the rest of the Engineering team

  • Collaborate with Data Analysts, Data Engineers, and business stakeholders to deliver trusted and actionable data

🧰 You will work with

dbt, BigQuery, Looker, GCP, Argo, Git, Claude

🧩 About you

To succeed in this job

  • You have at least 2 years of experience in Analytics Engineering, Data Engineering, Data Analytics, or a similar role.

  • You have practical experience with dbt, including models, tests, and documentation.

  • You have a good understanding of data modeling concepts such as facts, dimensions, keys, and relationships.

  • You have experience with Git and pull-request-based development, excellent communication skills, and the ability to collaborate with technical and business teams. You are fluent in English.

And it will be nice if you also

  • You are familiar with BigQuery, Looker, GCP, and Airflow or Argo.

  • You have knowledge of Python.

Don’t meet every single requirement? At Alma, we believe great hires come from diverse paths. If this role excites you, we encourage you to apply. We value potential, curiosity and the ability to grow as much as experience.

🧘 What’s in it for you

If you join, you will be able to grow and impact on:

  • The opportunity to shape analytics engineering practices within a growing and experienced central Data team

  • Exposure to modern data tools including dbt, Argo, Claude, GCP

  • A collaborative environment focused on improving data reliability, data literacy, and self-service analytics

🤑 Compensation & benefits

  • Competitive salary based on 12 months

  • Profit-sharing and employee savings plan

  • Health insurance: 100% covered by Alma including family package

  • Disability insurance: 100% covered by Alma

  • Sport: partnerships with Gymlib and Classpass, or €30/month reimbursement for your sports activities

  • Maternity/paternity leave: salary maintained at 100% during leave with no seniority requirement. Return to work at 4/5 schedule paid at 100% for 8 weeks.

  • Sustainable Mobility Package (FMD): €544.80/year (excluding full-remote contracts)

  • Meal vouchers: €10/day, 50% covered by Alma

  • Mental health: free access to MindDay platform

  • Paid time off: 25 days/year (+ additional paid leave granted for employees on executive contracts)

  • Access to our Learning & Development Platform

  • 2 weeks of full remote possible per year in summer

🎯 Interview Process

  • Video call with a Talent Acquisition team member to understand your path, motivation & present you the role.

  • Video call with your future manager to deep dive the role, the team, your profile and answer all your questions.

  • Case study presentation with 2 – 3 team members (ideally in house) to assess your practical knowledge.

  • 1 or 2 additional interviews customized to the role’s level to further assess your skills and team fit.

🌍 Diversity & Inclusion

At Alma, we believe that diversity fuels innovation and makes our community stronger. We are committed to building a workplace where every person feels seen, respected, and empowered to do their best work whatever their gender, background, ethnicity, age, sexual orientation, religion, disability or lived experience. As an equal opportunity employer, we welcome applicants from all walks of life, and all employment decisions are made based on qualifications, merit, and business needs.

Apply now >

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