Senior Big Data Engineer – Spark, Lakehouse & Cloud

Odaseva; Paris; Hybride; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Odaseva, based in Paris, is a SaaS company delivering secure data management for Salesforce environments. Join our R&D team to help shape the future of our data platform and work in a hybrid Paris-based role.

You will design, build, and optimize scalable Spark-based data pipelines for large-scale data lake ingestion using Databricks, Snowflake, and cloud services, with emphasis on governance, security, and performance.

Qualifications

• 7+ years of experience in data engineering or backend data platforms.
• Hands-on experience building and operating big data pipelines.
• Deep knowledge of at least one data lake platform.
• Strong Spark, Delta Lake or Iceberg expertise.
• Strong Python/Java and SQL, cloud infra and IaC/observability.
• Understanding of cost management, data security, governance and modeling.
• Equivalent engineering degree or Master’s in CS/DS/Applied Math.
• Fluent in English and French.

Responsabilités

• Data Pipeline Development & Operations: design, build, monitor Spark pipelines for large-volume ingestion.
• Platform & Cost Optimization: improve performance, reliability, and costs of pipelines.
• Databricks, Snowflake & Cloud Engineering: leverage Databricks, Snowflake, AWS components.
• Lakehouse Architecture: manage Delta Lake or Iceberg tables.
• Secure Data Management: apply governance and security across storage and compute.

Connaissances

Data engineering

Big data pipelines

Python

Java

SQL

Cloud

IaC/Observability

English & French comms

Formation

Master’s degree in Computer Science, Data Science, or Applied Mathematics

Outils

Databricks

Snowflake

AWS Redshift

Delta Lake

Apache Iceberg

Spark

AWS S3

Athena

Glue

Description du poste

Odaseva, based in Paris, is a SaaS company delivering secure data management for Salesforce environments. Join our R&D team to help shape the future of our data platform and work in a hybrid Paris-based role.

You will design, build, and optimize scalable Spark-based data pipelines for large-scale data lake ingestion using Databricks, Snowflake, and cloud services, with emphasis on governance, security, and performance.