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Senior Data Engineer

Convey -- US

Full-time
USA
python
sql
aws
postgresql
mysql
The job listing has expired. Unfortunately, the hiring company is no longer accepting new applications.

To see similar active jobs please follow this link: Remote Development jobs

Company

Convey -- US

 

Job Description

 

We are seeking a highly skilled Senior Data Engineer with expertise in SQL, Python and PySpark, with extensive knowledge and practical experience in utilizing AWS services. The ideal candidate will have a strong background in data engineering, with a focus on building scalable and efficient data pipelines. The person in this role will work with a wide array of healthcare data for ingestion, processing and consumption including but not limited to eligibility, claims, payments and risk adjustment.

 

KEY 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, Athena, 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 proactively identify and address data quality issues and performance bottlenecks.

 

EDUCATION AND EXPERIENCE:               

  • Minimum of 5 years of experience in data engineering, with a focus on building and optimizing data pipelines.
  • Expertise in Python programming and hands-on experience with SQL and PySpark for data processing and analysis.
  • Proficiency in Python frameworks and libraries for scientific computing (e.g. Numpy, Pandas, SciPy, Pytorch, Pyarrow).
  • Strong understanding of AWS services and experience in deploying data solutions on cloud platforms.
  • Experience working with healthcare data, including but not limited to eligibility, claims, payments, and risk adjustment datasets.
  • Expertise in modeling data in relational databases (e.g., PostgreSQL, MySQL) and file-based databases, ETL processes and data warehousing concepts.
  • Proven track record of designing, implementing, and troubleshooting ETL processes and processing scripts using Python and PySpark.
  • Excellent problem-solving skills and the ability to work independently as well as part of a team.
  • Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
  • Relevant certifications in AWS or data engineering would be a plus.

About Us

Convey is an analytics solution company focused on helping providers and health plans deliver improved financial and medical cost outcomes. Convey's Pareto IntelligenceTM was designed to help our health plan clients solve critical financial and business challenges in a post PPACA (Patient Protection and Affordable Care Act) world.

About the job

Full-time
USA
Posted 1 year ago
python
sql
aws
postgresql
mysql
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Senior Data Engineer

Convey -- US
The job listing has expired. Unfortunately, the hiring company is no longer accepting new applications.

To see similar active jobs please follow this link: Remote Development jobs

Company

Convey -- US

 

Job Description

 

We are seeking a highly skilled Senior Data Engineer with expertise in SQL, Python and PySpark, with extensive knowledge and practical experience in utilizing AWS services. The ideal candidate will have a strong background in data engineering, with a focus on building scalable and efficient data pipelines. The person in this role will work with a wide array of healthcare data for ingestion, processing and consumption including but not limited to eligibility, claims, payments and risk adjustment.

 

KEY 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, Athena, 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 proactively identify and address data quality issues and performance bottlenecks.

 

EDUCATION AND EXPERIENCE:               

  • Minimum of 5 years of experience in data engineering, with a focus on building and optimizing data pipelines.
  • Expertise in Python programming and hands-on experience with SQL and PySpark for data processing and analysis.
  • Proficiency in Python frameworks and libraries for scientific computing (e.g. Numpy, Pandas, SciPy, Pytorch, Pyarrow).
  • Strong understanding of AWS services and experience in deploying data solutions on cloud platforms.
  • Experience working with healthcare data, including but not limited to eligibility, claims, payments, and risk adjustment datasets.
  • Expertise in modeling data in relational databases (e.g., PostgreSQL, MySQL) and file-based databases, ETL processes and data warehousing concepts.
  • Proven track record of designing, implementing, and troubleshooting ETL processes and processing scripts using Python and PySpark.
  • Excellent problem-solving skills and the ability to work independently as well as part of a team.
  • Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
  • Relevant certifications in AWS or data engineering would be a plus.

About Us

Convey is an analytics solution company focused on helping providers and health plans deliver improved financial and medical cost outcomes. Convey's Pareto IntelligenceTM was designed to help our health plan clients solve critical financial and business challenges in a post PPACA (Patient Protection and Affordable Care Act) world.

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