Data Analytics Engineer (Snowflake, Airflow, dbt, Tableau)

Quick Facts

• Start: ASAP

• Mission duration: 2 months, renewable

• Work mode: 2 days/week remote

• Location: Issy-les-Moulineaux

Description

As part of the optimization and unification of cross-entity analytics capabilities, this role focuses on integrating, modeling, and delivering strategic Sustainability data. You will build scalable data connections and ingestion pipelines from multiple corporate sources, then model and govern the data in Snowflake for analysis and reporting.

Responsibilities

• Establish and secure robust, scalable technical connections to identified source systems (e.g., Resource Advisor, internal reference datasets).

• Extract and load data from key corporate functional domains (Finance, HR, reference data, Procurement, etc.).

• Design and implement automated ingestion pipelines ensuring data integrity and freshness.

• Structure and model data in a Snowflake Data Warehouse using logical, modular, reusable, analysis-optimized designs.

• Implement data governance mechanisms: metadata management, refresh logic, data quality tracking, and error handling.

• Develop data views and aggregates tailored to Sustainability reporting needs for the department and regional collaborators.

• Document ingestion pipelines, data models (logical/physical), transformation rules, and recovery points to support maintainability and transferability.

Benefits

• Renewable short mission (2 months)

• Hybrid setup with 2 days/week remote work

Requirements

• Mastery of data ingestion and transformation techniques in a cloud environment (Snowflake).

• Strong analytical data modeling skills (dimensional modeling, Data Vault, medallion, or other data-warehouse architectures).

• Excellent practices in pipeline orchestration, code versioning, and technical/functional documentation.

• Ability to work effectively within an Agile team following Scrum.

• High autonomy and initiative, with effective interaction with technical teams and business stakeholders.

• Capability to translate complex business requirements into technical data solutions.