Data Engineer

This is a fully remote position, open to applicants in France.

📋 Description

• Design and implement scalable, cloud-native data pipelines for both batch and streaming workloads

• Assist in the establishment of data ingestion frameworks for handling structured, semi-structured, and unstructured data

• Create APIs and integration services to facilitate data exchange among internal systems

• Collaborate with Senior Engineers to enhance platform scalability and reliability across global operations

• Aid in deploying database and storage solutions across relational, NoSQL, and data lake architectures

• Construct metadata-driven frameworks for data ingestion and transformation

• Help ensure that data schemas are conducive to analytics, AI/ML, and business applications

• Establish data quality frameworks, validation rules, and automated verification processes

• Develop reusable components for data transformation to standardize processing

• Support data lineage, cataloging, and governance capabilities with oversight

• Guarantee data privacy, protection, and compliance with regulations

• Create high-throughput distributed solutions for data processing

• Optimize data pipelines for enhanced performance, cost-effectiveness, and resilience

• Contribute to observability and monitoring to ensure pipeline health, data drift, and SLA adherence

• Design caching, partitioning, and indexing strategies to enhance query performance

• Empower data scientists with curated datasets and feature pipelines

• Develop feature stores suitable for real-time or batch processing

• Integrate data workflows with MLOps and model deployment systems with guidance

• Generate datasets that are ready for visualization in BI tools and dashboards

• Implement security measures including role-based access control, encryption, and secure data-sharing practices

• Ensure adherence to FDA/GxP, GDPR, HIPAA, and other regulatory standards

• Develop solutions for audit trails, data retention, and disaster recovery

• Stay updated on advancements in data engineering, AI, and cloud technologies

• Share knowledge and promote continuous improvement across data engineering practices

⛳️ Requirements

• Proficient understanding of cloud-native data platforms and serverless architectures (Azure, AWS)

• Solid grasp of CI/CD and DevOps principles

• Knowledge of data modeling concepts

• Familiarity with API design patterns

• Experience with streaming platforms (Kafka, Kinesis, Pub/Sub, Event Hubs)

• Strong proficiency in SQL

• Effective communication skills with the ability to collaborate across technical and business teams

• Experience in orchestrating data pipelines (e.g., Airflow, Prefect, Dagster)

• Familiarity with scalable data processing frameworks (Spark, Flink, Beam, Databricks)

• Background in data engineering or a related technical field

• Exposure to cloud-native data platforms (Azure, AWS, or GCP)

• Knowledge of modern ELT/ETL tools and distributed data processing

• Proficient in Python and SQL, with optional skills in third-generation programming languages

• Familiarity with modern data warehousing and lakehouse platforms

• Knowledge of analytics tools (Power BI, Tableau, Looker) is an advantage

• Bachelor's Degree in Computer Science, Data Engineering, Software Engineering, or a related field

• Fluent in English

🏝️ Benefits

• Comprehensive health insurance coverage

• Opportunities for professional development and training

• Flexible working hours and remote working options

• Engaging work environment with a focus on collaboration

• Competitive salary and performance-based bonuses