Analytics Engineer: Build Trusted Data & Self‑Service Analytics

Alma; Paris; Hybride; EUR 65 000 - 90 000; Plein temps

Avantages offerts par ce poste

Health insurance

Disability insurance

Sport benefits

Paid time off

Remote work options

Learning & Development

Meal vouchers

Résumé du poste

Alma in Paris is seeking an Analytics Engineer to strengthen the data foundations that support reporting, analytics, and operational processes. You will join a central Data team of six Analysts and work at the intersection of data engineering, analytics, and business teams.

You will transform raw data into trusted datasets, build reusable models in dbt and BigQuery, and improve data lineage and governance to empower self-service analytics across the organization.

Qualifications

• At least 2 years of experience in Analytics Engineering, Data Engineering, or a similar role.
• Practical experience with dbt, including models, tests, and documentation.
• Strong understanding of data modeling concepts such as facts, dimensions, keys and relationships.
• Experience with Git and pull-request based development; fluent in English; able to collaborate with technical and business teams.

Responsabilités

• Build 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 important tables.
• Enable self-service and conversational analytics for business teams.

Connaissances

dbt

BigQuery

Looker

GCP

Argo

Git

Claude

Python

Outils

BigQuery

Looker

GCP

Argo

Claude

Description du poste

Alma in Paris is seeking an Analytics Engineer to strengthen the data foundations that support reporting, analytics, and operational processes. You will join a central Data team of six Analysts and work at the intersection of data engineering, analytics, and business teams.

You will transform raw data into trusted datasets, build reusable models in dbt and BigQuery, and improve data lineage and governance to empower self-service analytics across the organization.