Remote Senior Data Engineer: Data Pipelines & Attribution

Jobgether; France; À distance; EUR 70 000 - 100 000; Plein temps

Avantages offerts par ce poste

Remote work

Flexible hours

35-hour workweek (Jul-Aug)

Private health insurance

Training budget

Birthday day off

Barcelona office access

Résumé du poste

Jobgether seeks a Senior Data Engineer - Mobile Apps based in France to build and operate reliable data infrastructure supporting marketing, payments, product analytics, and business decision-making. You will design data pipelines ingesting information from advertising platforms, payment systems, and product backends into modern cloud data environments using Databricks, Unity Catalog, and Delta.

Collaboration across Analytics, Marketing, Data Science, Product, and Engineering is essential to

Qualifications

• Proven experience in data engineering with hands-on Python, SQL, Spark, and Databricks.
• Experience with Databricks Unity Catalog and Delta.
• Experience with Apache Airflow for workflow orchestration.

Responsabilités

• Build, maintain, and operate data pipelines for daily reporting, attribution, and LTV.
• Ingest and transform data from ads, payments, and product backends into Databricks environments.
• Orchestrate data workflows with Airflow to ensure timely, accurate jobs.
• Maintain silver and gold data tables with quality checks and monitoring.
• Collaborate with Analytics, Marketing, Data Science, Product, and Engineering.

Connaissances

Python

SQL

Spark

Databricks

Outils

Databricks Unity Catalog

Delta

Apache Airflow

Google Cloud Platform

BigQuery

dbt

Description du poste

Jobgether seeks a Senior Data Engineer - Mobile Apps based in France to build and operate reliable data infrastructure supporting marketing, payments, product analytics, and business decision-making. You will design data pipelines ingesting information from advertising platforms, payment systems, and product backends into modern cloud data environments using Databricks, Unity Catalog, and Delta.

Collaboration across Analytics, Marketing, Data Science, Product, and Engineering is essential to