Analytics Engineer

Remote Jobs; France; Hybride; EUR 65 000 - 90 000; Plein temps

Avantages offerts par ce poste

Health insurance

Meal vouchers €10/day

2 weeks remote per year

Résumé du poste

Alma is looking for an Analytics Engineer to strengthen data foundations and enable self-serve analytics across Finance, Product, Marketing, Risk, and Operations. You will transform raw data into trusted datasets, contribute to governance, and collaborate with data analysts and engineers.

The role supports a hybrid model based in Paris, with full remote options in France. You will work at the intersection of Data Engineering, Data Analytics, and business teams, building scalable data assets and

Qualifications

• At least 2 years in Analytics Engineering, Data Engineering, or a similar role.
• Practical experience with dbt (models, tests, documentation).
• Understanding of data modeling concepts (facts, dimensions, keys, relationships).
• Experience with Git and PR-based development; fluent in English.

Responsabilités

• 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 data lineage, ownership, and discoverability of key tables.
• Strengthen semantic layer and ensure consistent metric definitions.

Connaissances

Analytical thinking

Collaborative

English fluency

Outils

dbt

BigQuery

Looker

GCP

Argo

Git

Claude

Python

Description du poste

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.

What's in it for you

• 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 the 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.