This role focuses on building robust Python APIs that leverage Spark for large-scale data processing. It offers the chance to work with distributed computing frameworks and contribute to cutting‑edge data solutions. Candidates will collaborate with data engineering and machine‑learning teams on real‑world projects.
What You’ll Do
- Design and implement scalable Python APIs on Apache Spark.
- Develop PySpark pipelines for data ingestion and transformation.
- Optimize Spark jobs for performance and resource usage.
- Collaborate with data engineers to refine data models.
- Conduct unit testing and code reviews for API components.
- Document API interfaces and usage guidelines.
What You Need
- Proficiency in Python programming.
- In‑depth knowledge of Apache Spark and PySpark.
- Experience designing data pipelines for large‑scale processing.
- Strong understanding of data engineering principles.
- Ability to optimize distributed computations.
- 6–8 years of professional software development experience.
- Familiarity with machine‑learning data workflows.
The Opportunity
This contract role allows you to contribute to high‑impact data projects in an on‑site environment. You’ll work with a global tech team and help drive innovation in data engineering.