Data Engineer
Design, build, and maintain scalable ETL/ELT pipelines. Leverage Databricks and modern data platforms to manage and process data. Collaborate with cross-functional teams to ensure data solutions meet business requirements. Optimize data processing workflows for performance and scalability. Hybrid role.
Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources.
- Leverage Databricks and other modern data platforms to manage, transform, and process data.
- Collaborate with software teams to understand data needs and ensure data solutions meet business requirements.
- Optimize data processing workflows for performance and scalability.
Requirements
- 4+ years of experience in Data Engineering, including cloud-based data solutions.
- Proven expertise in implementing large-scale data solutions.
- Proficiency in Python, PySpark.
- Experience with ETL/ELT processes.
- Experience with cloud technologies such as Databricks (Apache Spark).
- Strong analytical and problem-solving skills.
- Experience leading and designing data solutions end-to-end.
Nice to have
- Familiarity with on-premise or cloud storage systems.
- Excellent communication and collaboration skills.