Our client is a leading global technology company that operates one of the world's largest consumer and developer platforms, serving billions of users worldwide. Through its digital ecosystem, the company empowers developers and partners to build engaging experiences, reach global audiences, and drive innovation at scale.
They are currently seeking a Data Engineer to design, build, and optimize scalable data platforms and pipelines that support analytics, reporting, and machine learning initiatives.
This is an 8-months contract.
Responsibilities
- Design, build, and maintain scalable, reliable data pipelines and ETL/ELT workflows.
- Develop and optimize large-scale data models, warehouse architectures, and data processing systems for performance and scalability.
- Collaborate with Data Scientists, Product Managers, and Software Engineers to deliver robust data solutions.
- Implement data quality frameworks, including monitoring, validation, alerting, and anomaly detection.
- Ensure best practices in data governance, privacy compliance, and data lifecycle management.
- Continuously improve pipeline performance, automation, and operational efficiency.
Requirements
- 5+ years of experience in Data Engineering or a related technical role.
- Expert-level SQL with experience optimizing complex, production-grade data pipelines.
- Advanced Python for pipeline development, orchestration, and automation.
- Strong experience with Spark and distributed data processing frameworks.
- Proven experience building and maintaining scalable ETL/ELT pipelines from scratch.
- Solid understanding of data modeling, including dimensional modeling, star/snowflake schemas, and Data Vault concepts.
- Experience with large-scale data warehouses such as Hive, Presto, or similar technologies.
- Knowledge of data quality, governance, and privacy best practices.
- Experience leveraging AI-assisted development tools for pipeline development, logging, and dashboard creation is a plus.