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# Odaseva EnterpriseData Platform

- **Company:** Odaseva's R&d
- **Location:** Paris, France (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Microsoft Azure, Program Optimization, Customer Data Management, Information Engineering, Data Governance, Data Security, Data Sharing, Python (Programming Language), SQL Databases, Snowflake, Apache Spark, Backend, Data Lakes, Information Technology, Data Management, Data Pipelines, Databricks
- **Published:** September 5, 2026
- **Apply:** https://startup.jobs/data-engineer-odaseva-7947662

## About the Role

* Equivalent engineering school degree, or a Master's degree in Computer Science, Data Science, or Applied Mathematics.
 * 7-12 years in data engineering or backend data platforms.
 * Strong Python and SQL; experience with Spark and modern ELT/Orchestration (e.g., dbt, Airflow).
 * Hands-on with Databricks and/or Snowflake in production.
 * Experience on AWS (S3, Glue/Athena, Redshift, Lambda) and lakehouse formats (Iceberg or Delta Lake).
 * Familiarity with data security, governance, and compliance.
 * Proven experience with data modeling.
 * Knowledge of cost management principles.
 * Salesforce data knowledge is a plus, not mandatory.
 * Foundational AI/ML understanding and motivation to contribute to early use cases.
 * Fluent in English and French, clear communication, ownership mindset, and collaborative approach.
 * Excellent interpersonal skills and ability to interact with diverse business stakeholders

## Description

* Data Pipeline Development: Design, build, and maintain ingestion/processing pipelines at scale using Python/SQL and Spark; operate within a lakehouse stack (Apache Iceberg or Delta Lake).
 * Databricks & Snowflake Engineering: Implement and optimize workflows on Databricks (Jobs, Workflows, Delta) and/or Snowflake (Warehouses, Tasks, Streams) and/or native cloud provider solutions (AWS / AZURE).
 * Platform Optimization: Improve performance, reliability, and cost on AWS (S3, Redshift, Athena/Glue, Lambda), with strong observability and IaC practices.
 * Secure Data Management: Apply security-by-design, data governance, and compliance best practices across storage, compute, and sharing layers.
 * AI Use Case Enablement: Partner with Product team and R&D team to prepare data for initial AI/ML use cases (feature pipelines, data quality, lineage).
 * Data Sharing & Integration: Enable secure, efficient data access for customers via connectors, APIs, and lakehouse sharing patterns (e.g., Delta Sharing, Snowflake data sharing).


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