Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
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.
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:
3+ 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 and technologies such as Databricks (Apache Spark).
Strong analytical and problem-solving skills, with the ability to evaluate and interpret complex data.
Experience leading and designing data solutions end-to-end, integrating with multiple teams, and driving tasks to completion.
3+ 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 and technologies such as Databricks (Apache Spark).
Strong analytical and problem-solving skills, with the ability to evaluate and interpret complex data.
Experience leading and designing data solutions end-to-end, integrating with multiple teams, and driving tasks to completion.
This position is open to all candidates.
