Senior Data Engineer

1 month ago


Fort Lauderdale, United States Quess Full time

5 years experience

  • Top skills needed
  • Python, PySpark , frameworks and libraries (e.g. Numpy, Pandas, SciPy, Pytorch, Pyarrow)
  • Modeling data in relational databases (e.g., PostgreSQL, MySQL) and file-based databases, ETL processes and data warehousing concept
  • AWS services such as S3, Glue, EMR, and Redshift, deploying data solutions on cloud platforms
Experience working with healthcare data, including but not limited to eligibility, claims, payments, and risk adjustment datasets

DUTIES AND RESPONSIBILITIES:
  • Design, develop, and maintain robust data pipelines using Python and PySpark to process large volumes of healthcare data efficiently in a multitenant analytics platform.
  • Collaborate with cross-functional teams to understand data requirements, implement data models, and ensure data integrity throughout the pipeline.
  • Optimize data workflows for performance and scalability, considering factors such as data volume, velocity, and variety.
  • Implement best practices for data ingestion, transformation, and storage in AWS services such as S3, Glue, EMR, and Redshift.
  • Model data in relational databases (e.g., PostgreSQL, MySQL) and file-based databases to support data processing requirements.
  • Design and implement ETL processes using Python and PySpark to extract, transform, and load data from various sources into target databases.
  • Troubleshoot and enhance existing ETLs and processing scripts to improve efficiency and reliability of data pipelines.
  • Develop monitoring and alerting mechanisms to identify proactively and address data quality issues and performance bottlenecks.

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